0MQ_endpoint is any valid 0mq endpoint.

By Pieter Hintjens, CEO of iMatix

Please use the issue tracker for all comments and errata(勘误表). This version covers the latest stable(稳定的) release of ZeroMQ (3.2). If you are using older versions of ZeroMQ then some of the examples and explanations won't be accurate(精确的).

The Guide is originally in C, but also in PHP, Python, Lua, and Haxe. We've also translated most of the examples into C++, C#, CL, Delphi, Erlang, F#, Felix, Haskell, Java, Objective-C, Ruby, Ada, Basic, Clojure, Go, Haxe, Node.js, ooc, Perl, and Scala.

ZeroMQ (also known as ØMQ, 0MQ, or zmq) looks like an embeddable (可嵌入)networking library but acts like a concurrency (并发性)framework.(框架) It gives you sockets (插座)that carry atomic (原子的)messages across various transports like in-process, inter-process, TCP, and multicast.(多路广播) You can connect sockets N-to-N with patterns like fan-out, pub-sub, task distribution,(分布) and request-reply. It's fast enough to be the fabric (织物)for clustered (成群的)products. Its asynchronous (异步的)I/O model gives you scalable (可攀登的)multicore applications, built as asynchronous message-processing tasks. It has a score of language APIs and runs on most operating systems. ZeroMQ is from iMatix and is LGPLv3 open source.

We took a normal TCP socket, injected(注入) it with a mix of radioactive isotopes(同位素) stolen from a secret Soviet atomic research project, bombarded(轰炸) it with 1950-era cosmic(宇宙的) rays, and put it into the hands of a drug-addled comic(喜剧的) book author with a badly-disguised fetish(恋物) for bulging(膨胀) muscles(肌肉) clad(穿衣) in spandex(斯潘德克斯弹性纤维). Yes, ZeroMQ sockets are the world-saving superheroes(超级英雄) of the networking world.

Figure 1 - A terrible accident…

The Ø in ZeroMQ is all about tradeoffs. On the one hand this strange name lowers ZeroMQ's visibility (能见度)on Google and Twitter. On the other hand it annoys the heck (饲草架)out of some Danish folk who write us things like "ØMG røtfl", and "Ø is not a funny looking zero!" and "Rødgrød med fløde!", which is apparently(显然地) an insult(侮辱) that means "may your neighbours be the direct descendants(后裔) of Grendel!" Seems like a fair trade.

Originally the zero in ZeroMQ was meant as "zero broker" and (as close to) "zero latency(潜伏)" (as possible). Since then, it has come to encompass(包含) different goals: zero administration(管理), zero cost, zero waste. More generally, "zero" refers to the culture of minimalism(极简派艺术) that permeates(渗透) the project. We add power by removing complexity(复杂) rather than by exposing new functionality(功能).

This book is written for professional programmers who want to learn how to make the massively(大量地) distributed(分布式的) software that will dominate(控制) the future of computing. We assume(承担) you can read C code, because most of the examples here are in C even though ZeroMQ is used in many languages. We assume you care about scale(规模), because ZeroMQ solves that problem above all others. We assume you need the best possible results with the least possible cost, because otherwise you won't appreciate the trade-offs that ZeroMQ makes. Other than that basic background, we try to present all the concepts(观念) in networking and distributed computing you will need to use ZeroMQ.

Thanks to Andy Oram for making the O'Reilly book happen, and editing this text.

Thanks to Bill Desmarais, Brian Dorsey, Daniel Lin, Eric Desgranges, Gonzalo Diethelm, Guido Goldstein, Hunter Ford, Kamil Shakirov, Martin Sustrik, Mike Castleman, Naveen Chawla, Nicola Peduzzi, Oliver Smith, Olivier Chamoux, Peter Alexander, Pierre Rouleau, Randy Dryburgh, John Unwin, Alex Thomas, Mihail Minkov, Jeremy Avnet, Michael Compton, Kamil Kisiel, Mark Kharitonov, Guillaume Aubert, Ian Barber, Mike Sheridan, Faruk Akgul, Oleg Sidorov, Lev Givon, Allister MacLeod, Alexander D'Archangel, Andreas Hoelzlwimmer, Han Holl, Robert G. Jakabosky, Felipe Cruz, Marcus McCurdy, Mikhail Kulemin, Dr. Gergő Érdi, Pavel Zhukov, Alexander Else, Giovanni Ruggiero, Rick "Technoweenie", Daniel Lundin, Dave Hoover, Simon Jefford, Benjamin Peterson, Justin Case, Devon Weller, Richard Smith, Alexander Morland, Wadim Grasza, Michael Jakl, Uwe Dauernheim, Sebastian Nowicki, Simone Deponti, Aaron Raddon, Dan Colish, Markus Schirp, Benoit Larroque, Jonathan Palardy, Isaiah Peng, Arkadiusz Orzechowski, Umut Aydin, Matthew Horsfall, Jeremy W. Sherman, Eric Pugh, Tyler Sellon, John E. Vincent, Pavel Mitin, Min RK, Igor Wiedler, Olof Åkesson, Patrick Lucas, Heow Goodman, Senthil Palanisami, John Gallagher, Tomas Roos, Stephen McQuay, Erik Allik, Arnaud Cogoluègnes, Rob Gagnon, Dan Williams, Edward Smith, James Tucker, Kristian Kristensen, Vadim Shalts, Martin Trojer, Tom van Leeuwen, Hiten Pandya, Harm Aarts, Marc Harter, Iskren Ivov Chernev, Jay Han, Sonia Hamilton, Nathan Stocks, Naveen Palli, and Zed Shaw for their contributions to this work.

How to explain ZeroMQ? Some of us start by saying all the wonderful things it does. It's sockets(插座) on steroids(类固醇). It's like mailboxes with routing(路由选择). It's fast! Others try to share their moment of enlightenment(启迪), that zap-pow-kaboom satori(心灵之顿悟) paradigm-shift moment when it all became obvious. Things just become simpler. Complexity(复杂) goes away. It opens the mind. Others try to explain by comparison(比较). It's smaller, simpler, but still looks familiar. Personally, I like to remember why we made ZeroMQ at all, because that's most likely where you, the reader, still are today.

Programming is science dressed up as art because most of us don't understand the physics of software and it's rarely, if ever, taught. The physics of software is not algorithms(算法), data structures(结构), languages and abstractions(抽象). These are just tools we make, use, throw away. The real physics of software is the physics of people—specifically, (特别地)our limitations w(限制)hen it comes to complexity, and our desire to work together to solve large problems in pieces. This is the science of programming: make building blocks that people can understand and use easily, and people will work together to solve the very largest problems.

We live in a connected world, and modern software has to navigate(驾驶) this world. So the building blocks for tomorrow's very largest solutions(解决方案) are connected and massively(大量地) parallel(平行的). It's not enough for code to be "strong and silent" any more. Code has to talk to code. Code has to be chatty(饶舌的), sociable(社交的), well-connected. Code has to run like the human brain, trillions(万亿) of individual(个人的) neurons(神经元) firing off messages to each other, a massively parallel network with no central control, no single point of failure, yet able to solve immensely(极大地) difficult problems. And it's no accident that the future of code looks like the human brain, because the endpoints(端点) of every network are, at some level, human brains.

If you've done any work with threads, protocols(协议), or networks, you'll realize this is pretty much impossible. It's a dream. Even connecting a few programs across a few sockets is plain nasty(肮脏的) when you start to handle real life situations. Trillions? The cost would be unimaginable(不可思议的). Connecting computers is so difficult that software and services to do this is a multi-billion dollar business.

So we live in a world where the wiring is years ahead of our ability to use it. We had a software crisis(危机) in the 1980s, when leading software engineers like Fred Brooks believed there was no "Silver Bullet" to "promise even one order of magnitude(大小) of improvement(改进) in productivity(生产力), reliability(可靠性), or simplicity(朴素)".

Brooks missed(感到思念的) free and open source software, which solved that crisis, enabling us to share knowledge efficiently(有效地). Today we face another software crisis, but it's one we don't talk about much. Only the largest, richest firms can afford to create connected applications. There is a cloud, but it's proprietary(所有权). Our data and our knowledge is disappearing from our personal computers into clouds that we cannot access and with which we cannot compete. Who owns our social networks? It is like the mainframe-PC revolution in reverse(相反).

We can leave the political philosophy(哲学) for another book. The point is that while the Internet offers the potential(潜能) of massively(大量地) connected code, the reality is that this is out of reach for most of us, and so large interesting problems (in health, education, economics(经济学), transport, and so on) remain unsolved because there is no way to connect the code, and thus no way to connect the brains that could work together to solve these problems.

There have been many attempts to solve the challenge of connected code. There are thousands of IETF specifications(规格), each solving part of the puzzle. For application developers, HTTP is perhaps the one solution(解决方案) to have been simple enough to work, but it arguably(可论证地) makes the problem worse by encouraging developers and architects(建筑师) to think in terms of big servers and thin, stupid clients.

So today people are still connecting applications using raw UDP and TCP, proprietary protocols(协议), HTTP, and Websockets. It remains painful, slow, hard to scale(衡量), and essentially centralized(集中的). Distributed(分配) P2P architectures(建筑学) are mostly for play, not work. How many applications use Skype or Bittorrent to exchange data?

Which brings us back to the science of programming. To fix the world, we needed to do two things. One, to solve the general problem of "how to connect any code to any code, anywhere". Two, to wrap(包) that up in the simplest possible building blocks that people could understand and use easily.

It sounds ridiculously(可笑地) simple. And maybe it is. That's kind of the whole point.

We assume(承担) you are using at least version 3.2 of ZeroMQ. We assume you are using a Linux box or something similar. We assume you can read C code, more or less, as that's the default language for the examples. We assume that when we write constants like PUSH or SUBSCRIBE, you can imagine they are really called ZMQ_PUSH or ZMQ_SUBSCRIBE if the programming language needs it.

The examples live in a public GitHub repository. The simplest way to get all the examples is to clone(无性繁殖) this repository(贮藏室):

git clone --depth=1 https://github.com/imatix/zguide.git

Next, browse the examples subdirectory(子目录). You'll find examples by language. If there are examples missing in a language you use, you're encouraged to submit a translation. This is how this text became so useful, thanks to the work of many people. All examples are licensed under MIT/X11.

So let's start with some code. We start of course with a Hello World example. We'll make a client and a server. The client sends "Hello" to the server, which replies with "World". Here's the server in C, which opens a ZeroMQ socket(插座) on port 5555, reads requests on it, and replies with "World" to each request:

Figure 2 - Request-Reply

The REQ-REP socket(插座) pair is in lockstep(因循守旧). The client issues zmq_send() and then zmq_recv(), in a loop(环) (or once if that's all it needs). Doing any other sequence(序列) (e.g., sending two messages in a row) will result in a return code of -1 from the send or recv call. Similarly, the service issues zmq_recv() and then zmq_send() in that order, as often as it needs to.

ZeroMQ uses C as its reference(参考) language and this is the main language we'll use for examples. If you're reading this online, the link below the example takes you to translations into other programming languages. Let's compare the same server in C++:

You can see that the ZeroMQ API is similar in C and C++. In a language like PHP or Java, we can hide even more and the code becomes even easier to read:

The server in other languages:

Here's the client code:

Now this looks too simple to be realistic(现实的), but ZeroMQ sockets(插座) have, as we already learned, superpowers(超级大国). You could throw thousands of clients at this server, all at once, and it would continue to work happily and quickly. For fun, try starting the client and then starting the server, see how it all still works, then think for a second what this means.

Let us explain briefly what these two programs are actually doing. They create a ZeroMQ context(环境) to work with, and a socket. Don't worry what the words mean. You'll pick it up. The server binds(捆绑) its REP (reply) socket to port 5555. The server waits for a request in a loop(环), and responds(应答) each time with a reply. The client sends a request and reads the reply back from the server.

If you kill the server (Ctrl-C) and restart(重新启动) it, the client won't recover properly. Recovering from crashing processes isn't quite that easy. Making a reliable(可靠的) request-reply flow is complex(复杂的) enough that we won't cover it until Chapter 4 - Reliable Request-Reply Patterns.

There is a lot happening behind the scenes but what matters to us programmers is how short and sweet the code is, and how often it doesn't crash, even under a heavy load. This is the request-reply pattern, probably the simplest way to use ZeroMQ. It maps to RPC and the classic(经典的) client/server model.

ZeroMQ doesn't know anything about the data you send except its size in bytes. That means you are responsible(负责的) for formatting(格式化) it safely so that applications can read it back. Doing this for objects and complex data types is a job for specialized(专业的) libraries like Protocol Buffers. But even for strings, you need to take care.

In C and some other languages, strings are terminated(终止) with a null byte. We could send a string like "HELLO" with that extra null byte:

However, if you send a string from another language, it probably will not include that null byte. For example, when we send that same string in Python, we do this:

Then what goes onto the wire is a length (one byte for shorter strings) and the string contents as individual(个人的) characters.

Figure 3 - A ZeroMQ string

And if you read this from a C program, you will get something that looks like a string, and might by accident act like a string (if by luck the five bytes find themselves followed by an innocently(纯洁地) lurking(潜伏) null), but isn't a proper string. When your client and server don't agree on the string format, you will get weird(怪异的) results.

When you receive string data from ZeroMQ in C, you simply cannot trust that it's safely terminated(终止). Every single time you read a string, you should allocate(分配) a new buffer(缓冲区) with space for an extra byte, copy the string, and terminate it properly with a null.

So let's establish(建立) the rule that ZeroMQ strings are length-specified and are sent on the wire without a trailing null. In the simplest case (and we'll do this in our examples), a ZeroMQ string maps neatly to a ZeroMQ message frame(设计), which looks like the above figure—a length and some bytes.

Here is what we need to do, in C, to receive a ZeroMQ string and deliver it to the application as a valid C string:

This makes a handy helper function and in the spirit of making things we can reuse profitably(有利可图的), let's write a similar s_send function that sends strings in the correct ZeroMQ format, and package this into a header file we can reuse.

The result is zhelpers.h, which lets us write sweeter and shorter ZeroMQ applications in C. It is a fairly long source, and only fun for C developers, so read it at leisure(闲暇).

ZeroMQ does come in several versions and quite often, if you hit a problem, it'll be something that's been fixed in a later version. So it's a useful trick to know exactly what version of ZeroMQ you're actually linking with.

Here is a tiny program that does that:

The second classic(经典的) pattern is one-way data distribution(分布), in which a server pushes updates to a set of clients. Let's see an example that pushes out weather updates consisting of a zip code, temperature, and relative humidity(湿度). We'll generate(形成) random(随机的) values, just like the real weather stations do.

Here's the server. We'll use port 5556 for this application:

There's no start and no end to this stream of updates, it's like a never ending broadcast.

Here is the client application, which listens to the stream of updates and grabs anything to do with a specified(规定的) zip code, by default New York City because that's a great place to start any adventure:

Figure 4 - Publish-Subscribe

Note that when you use a SUB socket(插座) you must set a subscription(捐献) using zmq_setsockopt() and SUBSCRIBE, as in this code. If you don't set any subscription, you won't get any messages. It's a common mistake for beginners. The subscriber(订户) can set many subscriptions, which are added together. That is, if an update matches ANY subscription, the subscriber receives it. The subscriber can also cancel specific(特殊的) subscriptions. A subscription is often, but not necessarily a printable(印得出的) string. See zmq_setsockopt() for how this works.

The PUB-SUB socket pair is asynchronous(异步的). The client does zmq_recv(), in a loop(环) (or once if that's all it needs). Trying to send a message to a SUB socket will cause an error. Similarly, the service does zmq_send() as often as it needs to, but must not do zmq_recv() on a PUB socket(插座).

In theory with ZeroMQ sockets, it does not matter which end connects and which end binds(捆绑). However, in practice there are undocumented differences that I'll come to later. For now, bind the PUB and connect the SUB, unless your network design makes that impossible.

There is one more important thing to know about PUB-SUB sockets: you do not know precisely(精确地) when a subscriber(订户) starts to get messages. Even if you start a subscriber, wait a while, and then start the publisher, the subscriber will always miss the first messages that the publisher sends. This is because as the subscriber connects to the publisher (something that takes a small but non-zero time), the publisher may already be sending messages out.

This "slow joiner" symptom(症状) hits enough people often enough that we're going to explain it in detail. Remember that ZeroMQ does asynchronous(异步的) I/O, i.e., in the background. Say you have two nodes doing this, in this order:

• Subscriber connects to an endpoint(端点) and receives and counts messages.
• Publisher binds to an endpoint and immediately sends 1,000 messages.

Then the subscriber will most likely not receive anything. You'll blink(眨眼), check that you set a correct filter and try again, and the subscriber will still not receive anything.

Making a TCP connection involves(包含) to and from handshaking(握手) that takes several milliseconds(毫秒) depending on your network and the number of hops(蜱酒花) between peers(撒尿). In that time, ZeroMQ can send many messages. For sake(目的) of argument assume(承担) it takes 5 msecs to establish(建立) a connection, and that same link can handle 1M messages per second. During the 5 msecs that the subscriber is connecting to the publisher, it takes the publisher only 1 msec to send out those 1K messages.

In Chapter 2 - Sockets and Patterns we'll explain how to synchronize(合拍) a publisher and subscribers so that you don't start to publish data until the subscribers really are connected and ready. There is a simple and stupid way to delay the publisher, which is to sleep. Don't do this in a real application, though, because it is extremely fragile as well as inelegant(不雅的) and slow. Use sleeps to prove to yourself what's happening, and then wait for Chapter 2 - Sockets and Patterns to see how to do this right.

The alternative(二中择一) to synchronization(同步) is to simply assume that the published data stream is infinite(无限的) and has no start and no end. One also assumes that the subscriber doesn't care what transpired(发生) before it started up. This is how we built our weather client example.

So the client subscribes to its chosen zip code and collects 100 updates for that zip code. That means about ten million updates from the server, if zip codes are randomly(随便地) distributed(分布式的). You can start the client, and then the server, and the client will keep working. You can stop and restart(重新启动) the server as often as you like, and the client will keep working. When the client has collected its hundred updates, it calculates(计算) the average, prints it, and exits.

Some points about the publish-subscribe (pub-sub) pattern:

• A subscriber can connect to more than one publisher, using one connect call each time. Data will then arrive and be interleaved(交错) ("fair-queued") so that no single publisher drowns out the others.

• If a publisher has no connected subscribers, then it will simply drop all messages.

• If you're using TCP and a subscriber(订户) is slow, messages will queue up on the publisher. We'll look at how to protect publishers against this using the "high-water mark" later.

• From ZeroMQ v3.x, filtering happens at the publisher side when using a connected protocol(协议) (tcp:// or ipc://). Using the epgm:// protocol, filtering happens at the subscriber side. In ZeroMQ v2.x, all filtering happened at the subscriber side.

This is how long it takes to receive and filter 10M messages on my laptop(膝上型轻便电脑), which is an 2011-era Intel i5, decent(正派的) but nothing special:

$ time wuclient
Collecting updates from weather server...
Average temperature for zipcode '10001 ' was 28F
 
real    0m4.470s
user    0m0.000s
sys     0m0.008s

Figure 5 - Parallel(平行线) Pipeline

As a final example (you are surely getting tired of juicy code and want to delve(钻研) back into philological(文献学的) discussions about comparative(比较的) abstractive(摘要式的) norms(规范)), let's do a little supercomputing(超级计算). Then coffee. Our supercomputing application is a fairly typical(典型的) parallel processing model. We have:

• A ventilator(通风设备) that produces tasks that can be done in parallel
• A set of workers that process tasks
• A sink that collects results back from the worker processes

In reality, workers run on superfast(超快速) boxes, perhaps using GPUs (graphic(图表的) processing units) to do the hard math. Here is the ventilator(通风设备). It generates(形成) 100 tasks, each a message telling the worker to sleep for some number of milliseconds(毫秒):

Here is the worker application. It receives a message, sleeps for that number of seconds, and then signals that it's finished:

Here is the sink application. It collects the 100 tasks, then calculates(计算) how long the overall processing took, so we can confirm(确认) that the workers really were running in parallel(平行的) if there are more than one of them:

The average cost of a batch(一批) is 5 seconds. When we start 1, 2, or 4 workers we get results like this from the sink:

• 1 worker: total elapsed(消逝) time: 5034 msecs.
• 2 workers: total elapsed time: 2421 msecs.
• 4 workers: total elapsed time: 1018 msecs.

Let's look at some aspects(方面) of this code in more detail:

• The workers connect upstream(上游部门) to the ventilator(通风设备), and downstream(下游地) to the sink. This means you can add workers arbitrarily(武断地). If the workers bound to their endpoints(端点), you would need (a) more endpoints and (b) to modify(修改) the ventilator and/or the sink each time you added a worker. We say that the ventilator and sink are stable parts of our architecture(建筑学) and the workers are dynamic parts of it.

• We have to synchronize(合拍) the start of the batch with all workers being up and running. This is a fairly common gotcha(明白了) in ZeroMQ and there is no easy solution(解决方案). The zmq_connect method takes a certain time. So when a set of workers connect to the ventilator(通风设备), the first one to successfully connect will get a whole load of messages in that short time while the others are also connecting. If you don't synchronize(合拍) the start of the batch(一批) somehow, the system won't run in parallel(平行线) at all. Try removing the wait in the ventilator, and see what happens.

• The ventilator's PUSH socket(插座) distributes(分配) tasks to workers (assuming(承担) they are all connected before the batch starts going out) evenly. This is called load balancing and it's something we'll look at again in more detail.

• The sink's PULL socket collects results from workers evenly. This is called fair-queuing.

Figure 6 - Fair Queuing

The pipeline(管道) pattern also exhibits(展览品) the "slow joiner" syndrome(综合征), leading to accusations(控告) that PUSH sockets don't load balance properly. If you are using PUSH and PULL, and one of your workers gets way more messages than the others, it's because that PULL socket has joined faster than the others, and grabs a lot of messages before the others manage to connect. If you want proper load balancing, you probably want to look at the load balancing pattern in Chapter 3 - Advanced Request-Reply Patterns.

Having seen some examples, you must be eager to start using ZeroMQ in some apps. Before you start that, take a deep breath, chillax, and reflect(反映) on some basic advice that will save you much stress(压力) and confusion(混淆).

• Learn ZeroMQ step-by-step(按部就班的). It's just one simple API, but it hides a world of possibilities. Take the possibilities slowly and master each one.

• Write nice code. Ugly code hides problems and makes it hard for others to help you. You might get used to meaningless(无意义的) variable(变量的) names, but people reading your code won't. Use names that are real words, that say something other than "I'm too careless to tell you what this variable is really for". Use consistent(始终如一的) indentation(压痕) and clean layout(布局). Write nice code and your world will be more comfortable.

• Test what you make as you make it. When your program doesn't work, you should know what five lines are to blame. This is especially true when you do ZeroMQ magic, which just won't work the first few times you try it.

• When you find that things don't work as expected, break your code into pieces, test each one, see which one is not working. ZeroMQ lets you make essentially modular(模块化的) code; use that to your advantage.

• Make abstractions(抽象) (classes, methods, whatever) as you need them. If you copy/paste(张贴) a lot of code, you're going to copy/paste errors, too.

ZeroMQ applications always start by creating a context, and then using that for creating sockets(插座). In C, it's the zmq_ctx_new() call. You should create and use exactly one context in your process. Technically, the context is the container for all sockets in a single process, and acts as the transport for inproc sockets, which are the fastest way to connect threads in one process. If at runtime a process has two contexts, these are like separate ZeroMQ instances(实例). If that's explicitly(明确的) what you want, OK, but otherwise remember:

Call zmq_ctx_new() once at the start of a process, and zmq_ctx_destroy() once at the end.

If you're using the fork() system call, do zmq_ctx_new() after the fork and at the beginning of the child process code. In general, you want to do interesting (ZeroMQ) stuff(东西) in the children, and boring process management in the parent.

Classy(优等的) programmers share the same motto as classy hit men: always clean-up when you finish the job. When you use ZeroMQ in a language like Python, stuff gets automatically(自动地) freed for you. But when using C, you have to carefully free objects when you're finished with them or else you get memory leaks, unstable(不稳定的) applications, and generally bad karma(因果报应).

Memory leaks are one thing, but ZeroMQ is quite finicky(过分讲究的) about how you exit an application. The reasons are technical and painful, but the upshot(结果) is that if you leave any sockets(插座) open, the zmq_ctx_destroy() function will hang forever. And even if you close all sockets, zmq_ctx_destroy() will by default wait forever if there are pending(未决定的) connects or sends unless you set the LINGER to zero on those sockets before closing them.

The ZeroMQ objects we need to worry about are messages, sockets, and contexts(环境). Luckily it's quite simple, at least in simple programs:

• Use zmq_send() and zmq_recv() when you can, as it avoids the need to work with zmq_msg_t objects.

• If you do use zmq_msg_recv(), always release the received message as soon as you're done with it, by calling zmq_msg_close().

• If you are opening and closing a lot of sockets(插座), that's probably a sign that you need to redesign(重新设计) your application. In some cases socket handles won't be freed until you destroy the context(环境).

• When you exit the program, close your sockets and then call zmq_ctx_destroy(). This destroys the context.

This is at least the case for C development. In a language with automatic(自动的) object destruction(破坏), sockets and contexts will be destroyed as you leave the scope(范围). If you use exceptions(例外) you'll have to do the clean-up in something like a "final" block, the same as for any resource.

If you're doing multithreaded work, it gets rather more complex(复杂的) than this. We'll get to multithreading in the next chapter, but because some of you will, despite(尽管) warnings, try to run before you can safely walk, below is the quick and dirty guide to making a clean exit in a multithreaded ZeroMQ application.

First, do not try to use the same socket from multiple threads. Please don't explain why you think this would be excellent fun, just please don't do it. Next, you need to shut down each socket that has ongoing requests. The proper way is to set a low LINGER value (1 second), and then close the socket. If your language binding(结合) doesn't do this for you automatically(自动地) when you destroy a context, I'd suggest sending a patch(眼罩).

Finally, destroy the context. This will cause any blocking receives or polls(投票) or sends in attached(附加的) threads (i.e., which share the same context) to return with an error. Catch that error, and then set linger(徘徊) on, and close sockets in that thread, and exit. Do not destroy the same context(环境) twice. The zmq_ctx_destroy in the main thread will block until all sockets(插座) it knows about are safely closed.

Voila(瞧)! It's complex(复杂的) and painful enough that any language binding(有约束力的) author worth his or her salt will do this automatically(自动地) and make the socket closing dance unnecessary.

Now that you've seen ZeroMQ in action, let's go back to the "why".

Many applications these days consist of components(成分) that stretch(伸展) across some kind of network, either a LAN or the Internet. So many application developers end up doing some kind of messaging. Some developers use message queuing products, but most of the time they do it themselves, using TCP or UDP. These protocols(协议) are not hard to use, but there is a great difference between sending a few bytes from A to B, and doing messaging in any kind of reliable(可靠的) way.

Let's look at the typical(典型的) problems we face when we start to connect pieces using raw TCP. Any reusable(可重复使用的) messaging layer would need to solve all or most of these:

• How do we handle I/O? Does our application block, or do we handle I/O in the background? This is a key design decision. Blocking I/O creates architectures(建筑学) that do not scale(衡量) well. But background I/O can be very hard to do right.

• How do we handle dynamic(动态的) components, i.e., pieces that go away temporarily(临时地)? Do we formally(正式地) split components into "clients" and "servers" and mandate(授权) that servers cannot disappear? What then if we want to connect servers to servers? Do we try to reconnect(使再接合) every few seconds?

• How do we represent a message on the wire? How do we frame(有木架的) data so it's easy to write and read, safe from buffer(缓冲区) overflows(充满), efficient(有效率的) for small messages, yet adequate(充足的) for the very largest videos of dancing cats wearing party hats?

• How do we handle messages that we can't deliver immediately? Particularly, if we're waiting for a component to come back online? Do we discard(抛弃) messages, put them into a database, or into a memory queue?

• Where do we store message queues? What happens if the component reading from a queue is very slow and causes our queues to build up? What's our strategy(战略) then?

• How do we handle lost messages? Do we wait for fresh data, request a resend(再发), or do we build some kind of reliability(可靠性) layer that ensures(保证) messages cannot be lost? What if that layer itself crashes?

• What if we need to use a different network transport. Say, multicast(多路广播) instead of TCP unicast(单一传播)? Or IPv6? Do we need to rewrite the applications, or is the transport abstracted(摘要) in some layer?

• How do we route(路线) messages? Can we send the same message to multiple peers(撒尿)? Can we send replies back to an original requester?

• How do we write an API for another language? Do we re-implement a wire-level protocol or do we repackage(重新包装) a library? If the former, how can we guarantee(保证) efficient and stable(稳定的) stacks(堆)? If the latter, how can we guarantee interoperability(互操作性)?

• How do we represent data so that it can be read between different architectures(建筑学)? Do we enforce(实施) a particular encoding for data types? How far is this the job of the messaging system rather than a higher layer?

• How do we handle network errors? Do we wait and retry(重操作), ignore(驳回诉讼) them silently, or abort(中止计划)?

Take a typical(典型的) open source project like Hadoop Zookeeper and read the C API code in src/c/src/zookeeper.c. When I read this code, in January 2013, it was 4,200 lines of mystery(神秘) and in there is an undocumented, client/server network communication protocol(协议). I see it's efficient(有效率的) because it uses poll instead of select. But really, Zookeeper should be using a generic(类的) messaging layer and an explicitly(明确地) documented wire level protocol. It is incredibly(难以置信地) wasteful(浪费的) for teams to be building this particular wheel over and over.

But how to make a reusable(可重复使用的) messaging layer? Why, when so many projects need this technology, are people still doing it the hard way by driving TCP sockets(插座) in their code, and solving the problems in that long list over and over?

It turns out that building reusable messaging systems is really difficult, which is why few FOSS projects ever tried, and why commercial(商业的) messaging products are complex(复杂的), expensive, inflexible(顽固的), and brittle(易碎的). In 2006, iMatix designed AMQP which started to give FOSS developers perhaps the first reusable recipe(食谱) for a messaging system. AMQP works better than many other designs, but remains relatively complex, expensive, and brittle. It takes weeks to learn to use, and months to create stable(稳定的) architectures that don't crash when things get hairy(多毛的).

Figure 7 - Messaging as it Starts

Most messaging projects, like AMQP, that try to solve this long list of problems in a reusable way do so by inventing a new concept(观念), the "broker", that does addressing, routing(路由选择), and queuing. This results in a client/server protocol or a set of APIs on top of some undocumented protocol that allows applications to speak to this broker. Brokers are an excellent thing in reducing the complexity(复杂) of large networks. But adding broker-based messaging to a product like Zookeeper would make it worse, not better. It would mean adding an additional(附加的) big box, and a new single point of failure. A broker rapidly becomes a bottleneck(瓶颈) and a new risk(风险) to manage. If the software supports it, we can add a second, third, and fourth broker and make some failover(失效备援) scheme(计划). People do this. It creates more moving pieces, more complexity, and more things to break.

And a broker-centric setup(设置) needs its own operations team. You literally(照字面地) need to watch the brokers day and night, and beat them with a stick when they start misbehaving(作弊). You need boxes, and you need backup boxes, and you need people to manage those boxes. It is only worth doing for large applications with many moving pieces, built by several teams of people over several years.

Figure 8 - Messaging as it Becomes

So small to medium(中间的) application developers are trapped. Either they avoid network programming and make monolithic(整体的) applications that do not scale(衡量). Or they jump into network programming and make brittle(易碎的), complex(复杂的) applications that are hard to maintain(维持). Or they bet on a messaging product, and end up with scalable(可攀登的) applications that depend on expensive, easily broken technology. There has been no really good choice, which is maybe why messaging is largely stuck in the last century and stirs(搅拌) strong emotions(情感): negative(负的) ones for users, gleeful(愉快的) joy for those selling support and licenses.

What we need is something that does the job of messaging, but does it in such a simple and cheap way that it can work in any application, with close to zero cost. It should be a library which you just link, without any other dependencies(依赖性). No additional(附加的) moving pieces, so no additional risk(风险). It should run on any OS and work with any programming language.

And this is ZeroMQ: an efficient(有效率的), embeddable(可嵌入) library that solves most of the problems an application needs to become nicely elastic(有弹性的) across a network, without much cost.

Specifically:

• It handles I/O asynchronously(异步的), in background threads. These communicate with application threads using lock-free data structures(结构), so concurrent(并发的) ZeroMQ applications need no locks, semaphores(信号), or other wait states.

• Components(成分) can come and go dynamically(动态地) and ZeroMQ will automatically(自动地) reconnect(使再接合). This means you can start components in any order. You can create "service-oriented(服务型的) architectures(建筑学)" (SOAs) where services can join and leave the network at any time.

• It queues messages automatically when needed. It does this intelligently(聪明地), pushing messages as close as possible to the receiver before queuing them.

• It has ways of dealing with over-full queues (called "high water mark"). When a queue is full, ZeroMQ automatically blocks senders, or throws away messages, depending on the kind of messaging you are doing (the so-called "pattern").

• It lets your applications talk to each other over arbitrary(任意的) transports: TCP, multicast(多路广播), in-process, inter-process. You don't need to change your code to use a different transport.

• It handles slow/blocked readers safely, using different strategies(战略) that depend on the messaging pattern.

• It lets you route(路线) messages using a variety of patterns such as request-reply and pub-sub. These patterns are how you create the topology(拓扑学), the structure of your network.

• It lets you create proxies(代理人) to queue, forward, or capture(俘获) messages with a single call. Proxies can reduce the interconnection(互连) complexity(复杂) of a network.

• It delivers whole messages exactly as they were sent, using a simple framing(设计) on the wire. If you write a 10k message, you will receive a 10k message.

• It does not impose(强加) any format on messages. They are blobs from zero to gigabytes(十亿字节) large. When you want to represent data you choose some other product on top, such as msgpack, Google's protocol(协议) buffers(有软皮摩擦), and others.

• It handles network errors intelligently, by retrying(重试) automatically in cases where it makes sense.

• It reduces your carbon footprint(足迹). Doing more with less CPU means your boxes use less power, and you can keep your old boxes in use for longer. Al Gore would love ZeroMQ.

Actually ZeroMQ does rather more than this. It has a subversive(破坏性的) effect on how you develop network-capable applications. Superficially(表面的), it's a socket-inspired API on which you do zmq_recv() and zmq_send(). But message processing rapidly becomes the central loop(环), and your application soon breaks down into a set of message processing tasks. It is elegant(高雅的) and natural. And it scales(天平): each of these tasks maps to a node, and the nodes talk to each other across arbitrary(任意的) transports. Two nodes in one process (node is a thread), two nodes on one box (node is a process), or two nodes on one network (node is a box)—it's all the same, with no application code changes.

Let's see ZeroMQ's scalability(可扩展性) in action. Here is a shell(壳) script that starts the weather server and then a bunch(群) of clients in parallel(平行线):

wuserver &
wuclient 12345 &
wuclient 23456 &
wuclient 34567 &
wuclient 45678 &
wuclient 56789 &

As the clients run, we take a look at the active processes using the top command', and we see something like (on a 4-core box):

PID  USER  PR  NI  VIRT  RES  SHR S %CPU %MEM   TIME+  COMMAND
7136  ph   20   0 1040m 959m 1156 R  157 12.0 16:25.47 wuserver
7966  ph   20   0 98608 1804 1372 S   33  0.0  0:03.94 wuclient
7963  ph   20   0 33116 1748 1372 S   14  0.0  0:00.76 wuclient
7965  ph   20   0 33116 1784 1372 S    6  0.0  0:00.47 wuclient
7964  ph   20   0 33116 1788 1372 S    5  0.0  0:00.25 wuclient
7967  ph   20   0 33072 1740 1372 S    5  0.0  0:00.35 wuclient

Let's think for a second about what is happening here. The weather server has a single socket(插座), and yet here we have it sending data to five clients in parallel. We could have thousands of concurrent(并发的) clients. The server application doesn't see them, doesn't talk to them directly. So the ZeroMQ socket is acting like a little server, silently accepting client requests and shoving(挤) data out to them as fast as the network can handle it. And it's a multithreaded server, squeezing(挤) more juice out of your CPU.

These changes don't impact(影响) existing application code directly:

• Pub-sub filtering is now done at the publisher side instead of subscriber(订户) side. This improves performance significantly(意味深长地) in many pub-sub use cases. You can mix v3.2 and v2.1/v2.2 publishers and subscribers safely.

• ZeroMQ v3.2 has many new API methods (zmq_disconnect(), zmq_unbind(), zmq_monitor(), zmq_ctx_set(), etc.)

These are the main areas of impact(影响) on applications and language bindings(结合):

• Changed send/recv methods: zmq_send() and zmq_recv() have a different, simpler interface(界面), and the old functionality(功能) is now provided by zmq_msg_send() and zmq_msg_recv(). Symptom(症状): compile(编译) errors. Solution(解决方案): fix up your code.

• These two methods return positive(积极的) values on success, and -1 on error. In v2.x they always returned zero on success. Symptom: apparent(显然的) errors when things actually work fine. Solution: test strictly for return code = -1, not non-zero.

• zmq_poll() now waits for milliseconds(毫秒), not microseconds(微秒). Symptom: application stops responding(回答) (in fact responds 1000 times slower). Solution: use the ZMQ_POLL_MSEC macro(巨大的) defined(定义) below, in all zmq_poll calls.

• ZMQ_NOBLOCK is now called ZMQ_DONTWAIT. Symptom: compile failures on the ZMQ_NOBLOCK macro.

• The ZMQ_HWM socket(插座) option is now broken into ZMQ_SNDHWM and ZMQ_RCVHWM. Symptom(症状): compile(编译) failures on the ZMQ_HWM macro.

• Most but not all zmq_getsockopt() options are now integer(整数) values. Symptom: runtime error returns on zmq_setsockopt and zmq_getsockopt.

• The ZMQ_SWAP option has been removed. Symptom: compile failures on ZMQ_SWAP. Solution(解决方案): redesign(重新设计) any code that uses this functionality(功能).

For applications that want to run on both v2.x and v3.2, such as language bindings(结合), our advice is to emulate(仿真) v3.2 as far as possible. Here are C macro(巨大的) definitions(定义) that help your C/C++ code to work across both versions (taken from CZMQ):

Traditional network programming is built on the general assumption(假定) that one socket(插座) talks to one connection, one peer(贵族). There are multicast(多路广播) protocols(协议), but these are exotic(异国的). When we assume(承担) "one socket = one connection", we scale(衡量) our architectures(建筑学) in certain ways. We create threads of logic(逻辑) where each thread work with one socket, one peer. We place intelligence(智力) and state in these threads.

In the ZeroMQ universe, sockets are doorways(门口) to fast little background communications engines that manage a whole set of connections automagically(自动地) for you. You can't see, work with, open, close, or attach(依附) state to these connections. Whether you use blocking send or receive, or poll(投票), all you can talk to is the socket, not the connections it manages for you. The connections are private and invisible(无形的), and this is the key to ZeroMQ's scalability(可扩展性).

This is because your code, talking to a socket, can then handle any number of connections across whatever network protocols are around, without change. A messaging pattern sitting in ZeroMQ scales more cheaply than a messaging pattern sitting in your application code.

So the general assumption(假定) no longer applies. As you read the code examples, your brain will try to map them to what you know. You will read "socket(插座)" and think "ah, that represents a connection to another node". That is wrong. You will read "thread" and your brain will again think, "ah, a thread represents a connection to another node", and again your brain will be wrong.

If you're reading this Guide for the first time, realize that until you actually write ZeroMQ code for a day or two (and maybe three or four days), you may feel confused(混乱), especially by how simple ZeroMQ makes things for you, and you may try to impose(强加) that general assumption on ZeroMQ, and it won't work. And then you will experience your moment of enlightenment(启迪) and trust, that zap-pow-kaboom satori(心灵之顿悟) paradigm-shift moment when it all becomes clear.

In Chapter 1 - Basics we took ZeroMQ for a drive, with some basic examples of the main ZeroMQ patterns: request-reply, pub-sub, and pipeline(管道). In this chapter, we're going to get our hands dirty and start to learn how to use these tools in real programs.

We'll cover:

• How to create and work with ZeroMQ sockets.
• How to send and receive messages on sockets.
• How to build your apps around ZeroMQ's asynchronous(异步的) I/O model.
• How to handle multiple sockets in one thread.
• How to handle fatal(致命的) and nonfatal(非致命的) errors properly.
• How to handle interrupt signals like Ctrl-C.
• How to shut down a ZeroMQ application cleanly.
• How to check a ZeroMQ application for memory leaks.
• How to send and receive multipart messages.
• How to forward messages across networks.
• How to build a simple message queuing broker.
• How to write multithreaded applications with ZeroMQ.
• How to use ZeroMQ to signal between threads.
• How to use ZeroMQ to coordinate(调整) a network of nodes.
• How to create and use message envelopes for pub-sub.
• Using the HWM (high-water mark) to protect against memory overflows(充满).

To be perfectly honest, ZeroMQ does a kind of switch-and-bait on you, for which we don't apologize. It's for your own good and it hurts us more than it hurts you. ZeroMQ presents a familiar socket-based API, which requires great effort for us to hide a bunch(群) of message-processing engines. However, the result will slowly fix your world view about how to design and write distributed(分布式的) software.

Sockets(插座) are the de facto(事实上的) standard API for network programming, as well as being useful for stopping your eyes from falling onto your cheeks. One thing that makes ZeroMQ especially tasty to developers is that it uses sockets and messages instead of some other arbitrary(任意的) set of concepts(观念). Kudos(荣誉) to Martin Sustrik for pulling this off. It turns "Message Oriented Middleware", a phrase guaranteed(保证) to send the whole room off to Catatonia, into "Extra Spicy Sockets!", which leaves us with a strange craving(渴望) for pizza and a desire to know more.

Like a favorite dish, ZeroMQ sockets are easy to digest. Sockets have a life in four parts, just like BSD sockets:

• Creating and destroying sockets, which go together to form a karmic circle of socket life (see zmq_socket(), zmq_close()).

• Configuring(安装) sockets(插座) by setting options on them and checking them if necessary (see zmq_setsockopt(), zmq_getsockopt()).

• Plugging sockets into the network topology(拓扑学) by creating ZeroMQ connections to and from them (see zmq_bind(), zmq_connect()).

• Using the sockets to carry data by writing and receiving messages on them (see zmq_msg_send(), zmq_msg_recv()).

Note that sockets are always void(空的) pointers, and messages (which we'll come to very soon) are structures(结构). So in C you pass sockets as-such, but you pass addresses of messages in all functions that work with messages, like zmq_msg_send() and zmq_msg_recv(). As a mnemonic(记忆的), realize that "in ZeroMQ, all your sockets are belong(属于) to us", but messages are things you actually own in your code.

Creating, destroying, and configuring(安装) sockets(插座) works as you'd expect for any object. But remember that ZeroMQ is an asynchronous(异步的), elastic(有弹性的) fabric(织物). This has some impact(影响) on how we plug sockets into the network topology(拓扑学) and how we use the sockets after that.

To create a connection between two nodes, you use zmq_bind() in one node and zmq_connect() in the other. As a general rule of thumb(拇指), the node that does zmq_bind() is a "server", sitting on a well-known(著名的) network address, and the node which does zmq_connect() is a "client", with unknown or arbitrary(任意的) network addresses. Thus we say that we "bind(绑) a socket to an endpoint(端点)" and "connect a socket to an endpoint", the endpoint being that well-known network address.

ZeroMQ connections are somewhat different from classic(经典的) TCP connections. The main notable(值得注意的) differences are:

• They go across an arbitrary transport (inproc, ipc, tcp, pgm, or epgm). See zmq_inproc(), zmq_ipc(), zmq_tcp(), zmq_pgm(), and zmq_epgm().

• One socket(插座) may have many outgoing(外出的) and many incoming connections.

• There is no zmq_accept() method. When a socket is bound to an endpoint(端点) it automatically(自动地) starts accepting connections.

• The network connection itself happens in the background, and ZeroMQ will automatically(自动地) reconnect(使再接合) if the network connection is broken (e.g., if the peer(贵族) disappears and then comes back).

• Your application code cannot work with these connections directly; they are encapsulated(密封的) under the socket(插座).

Many architectures(建筑学) follow some kind of client/server model, where the server is the component(成分) that is most static, and the clients are the components that are most dynamic(动态的), i.e., they come and go the most. There are sometimes issues of addressing: servers will be visible(明显的) to clients, but not necessarily vice(副的) versa. So mostly it's obvious which node should be doing zmq_bind() (the server) and which should be doing zmq_connect() (the client). It also depends on the kind of sockets you're using, with some exceptions(例外) for unusual network architectures. We'll look at socket types later.

Now, imagine we start the client before we start the server. In traditional networking, we get a big red Fail flag. But ZeroMQ lets us start and stop pieces arbitrarily(武断地). As soon as the client node does zmq_connect(), the connection exists and that node can start to write messages to the socket. At some stage (hopefully before messages queue up so much that they start to get discarded(抛弃), or the client blocks), the server comes alive, does a zmq_bind(), and ZeroMQ starts to deliver messages.

A server node can bind(绑) to many endpoints(端点) (that is, a combination(结合) of protocol(协议) and address) and it can do this using a single socket. This means it will accept connections across different transports:

With most transports, you cannot bind(结合) to the same endpoint(端点) twice, unlike for example in UDP. The ipc transport does, however, let one process bind to an endpoint already used by a first process. It's meant to allow a process to recover after a crash.

Although ZeroMQ tries to be neutral(中立的) about which side binds and which side connects, there are differences. We'll see these in more detail later. The upshot(结果) is that you should usually think in terms of "servers" as static parts of your topology(拓扑学) that bind to more or less fixed endpoints, and "clients" as dynamic(动态的) parts that come and go and connect to these endpoints. Then, design your application around this model. The chances that it will "just work" are much better like that.

Sockets(插座) have types. The socket type defines(定义) the semantics(语义学) of the socket, its policies(政策) for routing(路由选择) messages inwards and outwards, queuing, etc. You can connect certain types of socket together, e.g., a publisher socket and a subscriber(订户) socket. Sockets work together in "messaging patterns". We'll look at this in more detail later.

It's the ability to connect sockets in these different ways that gives ZeroMQ its basic power as a message queuing system. There are layers on top of this, such as proxies(代理人), which we'll get to later. But essentially, with ZeroMQ you define your network architecture(建筑学) by plugging pieces together like a child's construction toy.

To send and receive messages you use the zmq_msg_send() and zmq_msg_recv() methods. The names are conventional(符合习俗的), but ZeroMQ's I/O model is different enough from the classic(经典的) TCP model that you will need time to get your head around it.

Figure 9 - TCP sockets(插座) are 1 to 1

Let's look at the main differences between TCP sockets and ZeroMQ sockets when it comes to working with data:

• ZeroMQ sockets carry messages, like UDP, rather than a stream of bytes as TCP does. A ZeroMQ message is length-specified binary(二进制的) data. We'll come to messages shortly; their design is optimized(最佳化的) for performance and so a little tricky(狡猾的).

• ZeroMQ sockets do their I/O in a background thread. This means that messages arrive in local input(投入) queues and are sent from local output queues, no matter what your application is busy doing.

• ZeroMQ sockets have one-to-N routing(路由选择) behavior(行为) built-in(嵌入的), according to the socket type.

The zmq_send() method does not actually send the message to the socket connection(s). It queues the message so that the I/O thread can send it asynchronously(异步的). It does not block except in some exception(例外) cases. So the message is not necessarily sent when zmq_send() returns to your application.

ZeroMQ provides a set of unicast(单一传播) transports (inproc, ipc, and tcp) and multicast(多路广播) transports (epgm, pgm). Multicast is an advanced technique that we'll come to later. Don't even start using it unless you know that your fan-out ratios(比率) will make 1-to-N unicast(单一传播) impossible.

For most common cases, use tcp, which is a disconnected TCP transport. It is elastic(有弹性的), portable, and fast enough for most cases. We call this disconnected(拆开) because ZeroMQ's tcp transport doesn't require that the endpoint(端点) exists before you connect to it. Clients and servers can connect and bind(捆绑) at any time, can go and come back, and it remains transparent(透明的) to applications.

The inter-process ipc transport is disconnected, like tcp. It has one limitation(限制): it does not yet work on Windows. By convention(大会) we use endpoint names with an ".ipc" extension(延长) to avoid potential(潜在的) conflict(冲突) with other file names. On UNIX systems, if you use ipc endpoints you need to create these with appropriate(适当的) permissions otherwise they may not be shareable(可分享的) between processes running under different user IDs. You must also make sure all processes can access the files, e.g., by running in the same working directory.

The inter-thread transport, inproc, is a connected signaling transport. It is much faster than tcp or ipc. This transport has a specific(特殊的) limitation(限制) compared to tcp and ipc: the server must issue a bind(捆绑) before any client issues a connect. This is something future versions of ZeroMQ may fix, but at present this defines(定义) how you use inproc sockets(插座). We create and bind one socket and start the child threads, which create and connect the other sockets.

A common question that newcomers to ZeroMQ ask (it's one I've asked myself) is, "how do I write an XYZ server in ZeroMQ?" For example, "how do I write an HTTP server in ZeroMQ?" The implication(含义) is that if we use normal sockets to carry HTTP requests and responses, we should be able to use ZeroMQ sockets to do the same, only much faster and better.

The answer used to be "this is not how it works". ZeroMQ is not a neutral(中立的) carrier: it imposes(利用) a framing(框架) on the transport protocols(协议) it uses. This framing is not compatible(兼容的) with existing protocols, which tend(照料) to use their own framing. For example, compare an HTTP request and a ZeroMQ request, both over TCP/IP.

Figure 10 - HTTP on the Wire

The HTTP request uses CR-LF as its simplest framing delimiter(划界), whereas(然而) ZeroMQ uses a length-specified frame. So you could write an HTTP-like protocol using ZeroMQ, using for example the request-reply socket(插座) pattern. But it would not be HTTP.

Figure 11 - ZeroMQ on the Wire

Since v3.3, however, ZeroMQ has a socket option called ZMQ_ROUTER_RAW that lets you read and write data without the ZeroMQ framing. You could use this to read and write proper HTTP requests and responses. Hardeep Singh contributed(贡献) this change so that he could connect to Telnet servers from his ZeroMQ application. At time of writing this is still somewhat experimental(实验的), but it shows how ZeroMQ keeps evolving(发展) to solve new problems. Maybe the next patch(眼罩) will be yours.

We said that ZeroMQ does I/O in a background thread. One I/O thread (for all sockets) is sufficient(足够的) for all but the most extreme(极端的) applications. When you create a new context(环境), it starts with one I/O thread. The general rule of thumb(拇指) is to allow one I/O thread per gigabyte(十亿字节) of data in or out per second. To raise the number of I/O threads, use the zmq_ctx_set() call before creating any sockets:

We've seen that one socket(插座) can handle dozens, even thousands of connections at once. This has a fundamental(基本的) impact(影响) on how you write applications. A traditional networked(网路的) application has one process or one thread per remote(遥远的) connection, and that process or thread handles one socket. ZeroMQ lets you collapse(倒塌) this entire structure(结构) into a single process and then break it up as necessary for scaling(缩放比例).

If you are using ZeroMQ for inter-thread communications only (i.e., a multithreaded application that does no external(外部的) socket I/O) you can set the I/O threads to zero. It's not a significant(重大的) optimization(最佳化) though, more of a curiosity(好奇).

Underneath(在…的下面) the brown paper wrapping(包装纸) of ZeroMQ's socket API lies the world of messaging patterns. If you have a background in enterprise messaging, or know UDP well, these will be vaguely(含糊地) familiar. But to most ZeroMQ newcomers, they are a surprise. We're so used to the TCP paradigm(范例) where a socket maps one-to-one to another node.

Let's recap(翻新的轮胎) briefly what ZeroMQ does for you. It delivers blobs of data (messages) to nodes, quickly and efficiently(有效地). You can map nodes to threads, processes, or nodes. ZeroMQ gives your applications a single socket API to work with, no matter what the actual transport (like in-process, inter-process, TCP, or multicast(多路广播)). It automatically(自动的) reconnects(使再接合) to peers(撒尿) as they come and go. It queues messages at both sender and receiver, as needed. It limits these queues to guard processes against running out of memory. It handles socket errors. It does all I/O in background threads. It uses lock-free techniques for talking between nodes, so there are never locks, waits, semaphores(信号), or deadlocks(僵局).

But cutting through that, it routes(路由) and queues messages according to precise(精确的) recipes(食谱) called patterns. It is these patterns that provide ZeroMQ's intelligence(智力). They encapsulate(压缩) our hard-earned experience of the best ways to distribute(分配) data and work. ZeroMQ's patterns are hard-coded but future versions may allow user-definable patterns.

ZeroMQ patterns are implemented(实施) by pairs of sockets(插座) with matching types. In other words, to understand ZeroMQ patterns you need to understand socket types and how they work together. Mostly, this just takes study; there is little that is obvious at this level.

The built-in(嵌入的) core ZeroMQ patterns are:

• Request-reply, which connects a set of clients to a set of services. This is a remote(遥远的) procedure(程序) call and task distribution(分布) pattern.

• Pub-sub, which connects a set of publishers to a set of subscribers(订阅). This is a data distribution pattern.

• Pipeline, which connects nodes in a fan-out/fan-in pattern that can have multiple steps and loops(环). This is a parallel(平行的) task distribution and collection pattern.

• Exclusive pair, which connects two sockets exclusively(唯一地). This is a pattern for connecting two threads in a process, not to be confused(混乱) with "normal" pairs of sockets.

We looked at the first three of these in Chapter 1 - Basics, and we'll see the exclusive pair pattern later in this chapter. The zmq_socket() man page is fairly clear about the patterns — it's worth reading several times until it starts to make sense. These are the socket combinations t(结合)hat are valid for a connect-bind pair (either side can bind):(结合)

• PUB and SUB
• REQ and REP
• REQ and ROUTER (take care, REQ inserts an extra null frame(框架))
• DEALER and REP (take care, REP assumes(承担) a null frame)
• DEALER and ROUTER
• DEALER and DEALER
• ROUTER and ROUTER
• PUSH and PULL
• PAIR and PAIR

You'll also see references(参考) to XPUB and XSUB sockets(插座), which we'll come to later (they're like raw versions of PUB and SUB). Any other combination(结合) will produce undocumented and unreliable(不可靠的) results, and future versions of ZeroMQ will probably return errors if you try them. You can and will, of course, bridge other socket types via code, i.e., read from one socket type and write to another.

These four core patterns are cooked into ZeroMQ. They are part of the ZeroMQ API, implemented(实施) in the core C++ library, and are guaranteed(保证) to be available in all fine retail(零售的) stores.

On top of those, we add high-level messaging patterns. We build these high-level patterns on top of ZeroMQ and implement them in whatever language we're using for our application. They are not part of the core library, do not come with the ZeroMQ package, and exist in their own space as part of the ZeroMQ community. For example the Majordomo pattern, which we explore in Chapter 4 - Reliable(可靠的) Request-Reply Patterns, sits in the GitHub Majordomo project in the ZeroMQ organization.

One of the things we aim to provide you with in this book are a set of such high-level patterns, both small (how to handle messages sanely(稳健地)) and large (how to make a reliable pub-sub architecture(建筑学)).

The libzmq core library has in fact two APIs to send and receive messages. The zmq_send() and zmq_recv() methods that we've already seen and used are simple one-liners(小笑话). We will use these often, but zmq_recv() is bad at dealing with arbitrary(任意的) message sizes: it truncates(把…截短) messages to whatever buffer(缓冲区) size you provide. So there's a second API that works with zmq_msg_t structures(结构), with a richer but more difficult API:

• Initialise a message: zmq_msg_init(), zmq_msg_init_size(), zmq_msg_init_data().
• Sending and receiving a message: zmq_msg_send(), zmq_msg_recv().
• Release a message: zmq_msg_close().
• Access message content: zmq_msg_data(), zmq_msg_size(), zmq_msg_more().
• Work with message properties: zmq_msg_get(), zmq_msg_set().
• Message manipulation: zmq_msg_copy(), zmq_msg_move().

On the wire, ZeroMQ messages are blobs of any size from zero upwards that fit in memory. You do your own serialization(序列化) using protocol(协议) buffers(有软皮摩擦), msgpack, JSON, or whatever else your applications need to speak. It's wise to choose a data representation(代表) that is portable, but you can make your own decisions about trade-offs.

In memory, ZeroMQ messages are zmq_msg_t structures(结构) (or classes depending on your language). Here are the basic ground rules for using ZeroMQ messages in C:

• You create and pass around zmq_msg_t objects, not blocks of data.

• To read a message, you use zmq_msg_init() to create an empty message, and then you pass that to zmq_msg_recv().

• To write a message from new data, you use zmq_msg_init_size() to create a message and at the same time allocate(分配) a block of data of some size. You then fill that data using memcpy, and pass the message to zmq_msg_send().

• To release (not destroy) a message, you call zmq_msg_close(). This drops a reference(参考), and eventually(最后的) ZeroMQ will destroy the message.

• To access the message content, you use zmq_msg_data(). To know how much data the message contains, use zmq_msg_size().

• Do not use zmq_msg_move(), zmq_msg_copy(), or zmq_msg_init_data() unless you read the man pages and know precisely(精确地) why you need these.

• After you pass a message to zmq_msg_send(), ØMQ will clear the message, i.e., set the size to zero. You cannot send the same message twice, and you cannot access the message data after sending it.

• These rules don't apply if you use zmq_send() and zmq_recv(), to which you pass byte arrays(数组), not message structures(结构).

If you want to send the same message more than once, and it's sizable(相当大的), create a second message, initialize(初始化) it using zmq_msg_init(), and then use zmq_msg_copy() to create a copy of the first message. This does not copy the data but copies a reference(参考). You can then send the message twice (or more, if you create more copies) and the message will only be finally destroyed when the last copy is sent or closed.

ZeroMQ also supports multipart messages, which let you send or receive a list of frames(框架) as a single on-the-wire message. This is widely used in real applications and we'll look at that later in this chapter and in Chapter 3 - Advanced Request-Reply Patterns.

Frames (also called "message parts" in the ZeroMQ reference manual(手工的) pages) are the basic wire format for ZeroMQ messages. A frame is a length-specified block of data. The length can be zero upwards. If you've done any TCP programming you'll appreciate why frames are a useful answer to the question "how much data am I supposed to read of this network socket(插座) now?"

There is a wire-level protocol called ZMTP that defines(定义) how ZeroMQ reads and writes frames on a TCP connection. If you're interested in how this works, the spec(投机) is quite short.

Originally, a ZeroMQ message was one frame, like UDP. We later extended(延伸) this with multipart messages, which are quite simply series of frames with a "more" bit set to one, followed by one with that bit set to zero. The ZeroMQ API then lets you write messages with a "more" flag and when you read messages, it lets you check if there's "more".

In the low-level ZeroMQ API and the reference manual, therefore, there's some fuzziness(绒毛的特性) about messages versus(对) frames. So here's a useful lexicon(词典):

• A message can be one or more parts.
• These parts are also called "frames(框架)".
• Each part is a zmq_msg_t object.
• You send and receive each part separately, in the low-level API.
• Higher-level APIs provide wrappers(包) to send entire multipart messages.

Some other things that are worth knowing about messages:

• You may send zero-length messages, e.g., for sending a signal from one thread to another.

• ZeroMQ guarantees(保证) to deliver all the parts (one or more) for a message, or none of them.

• ZeroMQ does not send the message (single or multipart) right away, but at some indeterminate(不确定的) later time. A multipart message must therefore fit in memory.

• A message (single or multipart) must fit in memory. If you want to send files of arbitrary(任意的) sizes, you should break them into pieces and send each piece as separate single-part messages. Using multipart data will not reduce memory consumption(消费).

• You must call zmq_msg_close() when finished with a received message, in languages that don't automatically(自动地) destroy objects when a scope(范围) closes. You don't call this method after sending a message.

And to be repetitive(重复的), do not use zmq_msg_init_data() yet. This is a zero-copy method and is guaranteed to create trouble for you. There are far more important things to learn about ZeroMQ before you start to worry about shaving off microseconds(微秒).

This rich API can be tiresome to work with. The methods are optimized(最佳化的) for performance, not simplicity(朴素). If you start using these you will almost definitely(清楚地) get them wrong until you've read the man pages with some care. So one of the main jobs of a good language binding(装订) is to wrap this API up in classes that are easier to use.

In all the examples so far, the main loop(环) of most examples has been:

1. Wait for message on socket(插座).
2. Process message.
3. Repeat.

What if we want to read from multiple endpoints(端点) at the same time? The simplest way is to connect one socket to all the endpoints and get ZeroMQ to do the fan-in for us. This is legal(法律的) if the remote(遥远的) endpoints are in the same pattern, but it would be wrong to connect a PULL socket to a PUB endpoint.

To actually read from multiple sockets all at once, use zmq_poll(). An even better way might be to wrap(包) zmq_poll() in a framework(框架) that turns it into a nice event-driven reactor, but it's significantly(重大的) more work than we want to cover here.

Let's start with a dirty hack, partly for the fun of not doing it right, but mainly because it lets me show you how to do nonblocking socket reads. Here is a simple example of reading from two sockets using nonblocking reads. This rather confused(混乱) program acts both as a subscriber(订户) to weather updates, and a worker for parallel(平行的) tasks:

The cost of this approach(方法) is some additional(附加的) latency(潜伏) on the first message (the sleep at the end of the loop(环), when there are no waiting messages to process). This would be a problem in applications where submillisecond latency was vital(至关重要的). Also, you need to check the documentation(文件材料) for nanosleep() or whatever function you use to make sure it does not busy-loop.

You can treat the sockets(插座) fairly by reading first from one, then the second rather than prioritizing(把…区分优先次序) them as we did in this example.

Now let's see the same senseless(愚蠢的) little application done right, using zmq_poll():

The items structure(结构) has these four members:

ZeroMQ lets us compose(构成) a message out of several frames(框架), giving us a "multipart message". Realistic applications use multipart messages heavily, both for wrapping(包装用的) messages with address information and for simple serialization(序列化). We'll look at reply envelopes later.

What we'll learn now is simply how to blindly and safely read and write multipart messages in any application (such as a proxy(代理人)) that needs to forward messages without inspecting them.

When you work with multipart messages, each part is a zmq_msg item. E.g., if you are sending a message with five parts, you must construct, send, and destroy five zmq_msg items. You can do this in advance (and store the zmq_msg items in an array(数组) or other structure(结构)), or as you send them, one-by-one.

Here is how we send the frames in a multipart message (we receive each frame into a message object):

Here is how we receive and process all the parts in a message, be it single part or multipart:

Some things to know about multipart messages:

• When you send a multipart message, the first part (and all following parts) are only actually sent on the wire when you send the final part.
• If you are using zmq_poll(), when you receive the first part of a message, all the rest has also arrived.
• You will receive all parts of a message, or none at all.
• Each part of a message is a separate zmq_msg item.
• You will receive all parts of a message whether or not you check the more property.
• On sending, ZeroMQ queues message frames(框架) in memory until the last is received, then sends them all.
• There is no way to cancel a partially(部分地) sent message, except by closing the socket(插座).

ZeroMQ aims for decentralized(分散的) intelligence(智力), but that doesn't mean your network is empty space in the middle. It's filled with message-aware infrastructure(基础设施) and quite often, we build that infrastructure with ZeroMQ. The ZeroMQ plumbing(垂直) can range from tiny pipes to full-blown(成熟的) service-oriented(服务型的) brokers. The messaging industry calls this intermediation, meaning that the stuff(东西) in the middle deals with either side. In ZeroMQ, we call these proxies(代理人), queues, forwarders, device(装置), or brokers, depending on the context(环境).

This pattern is extremely common in the real world and is why our societies and economies(经济) are filled with intermediaries(中间人) who have no other real function than to reduce the complexity(复杂) and scaling(衡量) costs of larger networks. Real-world intermediaries are typically(代表性地) called wholesalers(批发), distributors(经销商), managers, and so on.

One of the problems you will hit as you design larger distributed(分布式的) architectures(建筑学) is discovery. That is, how do pieces know about each other? It's especially difficult if pieces come and go, so we call this the "dynamic discovery problem".

There are several solutions(解决方案) to dynamic discovery. The simplest is to entirely avoid it by hard-coding (or configuring(安装)) the network architecture so discovery is done by hand. That is, when you add a new piece, you reconfigure(重新配置) the network to know about it.

Figure 12 - Small-Scale Pub-Sub Network

In practice, this leads to increasingly fragile and unwieldy(笨拙的) architectures. Let's say you have one publisher and a hundred subscribers(订阅). You connect each subscriber to the publisher by configuring a publisher endpoint(端点) in each subscriber. That's easy. Subscribers are dynamic; the publisher is static. Now say you add more publishers. Suddenly, it's not so easy any more. If you continue to connect each subscriber to each publisher, the cost of avoiding dynamic discovery gets higher and higher.

Figure 13 - Pub-Sub Network with a Proxy(代理人)

There are quite a few answers to this, but the very simplest answer is to add an intermediary(中间的); that is, a static point in the network to which all other nodes connect. In classic(经典的) messaging, this is the job of the message broker. ZeroMQ doesn't come with a message broker as such, but it lets us build intermediaries quite easily.

You might wonder, if all networks eventually(最后) get large enough to need intermediaries, why don't we simply have a message broker in place for all applications? For beginners, it's a fair compromise(妥协). Just always use a star topology(拓扑学), forget about performance, and things will usually work. However, message brokers are greedy things; in their role as central intermediaries, they become too complex(复杂的), too stateful(状态性的), and eventually a problem.

It's better to think of intermediaries as simple stateless(没有国家的) message switches(开关). A good analogy(类比) is an HTTP proxy; it's there, but doesn't have any special role. Adding a pub-sub proxy solves the dynamic discovery problem in our example. We set the proxy in the "middle" of the network. The proxy opens an XSUB socket(插座), an XPUB socket, and binds(捆绑) each to well-known(著名的) IP addresses and ports. Then, all other processes connect to the proxy, instead of to each other. It becomes trivial(不重要的) to add more subscribers or publishers.

Figure 14 - Extended(延伸) Pub-Sub

We need XPUB and XSUB sockets because ZeroMQ does subscription(捐献) forwarding from subscribers to publishers. XSUB and XPUB are exactly like SUB and PUB except they expose subscriptions as special messages. The proxy has to forward these subscription messages from subscriber side to publisher side, by reading them from the XPUB socket and writing them to the XSUB socket. This is the main use case for XSUB and XPUB.

In the Hello World client/server application, we have one client that talks to one service. However, in real cases we usually need to allow multiple services as well as multiple clients. This lets us scale(规模) up the power of the service (many threads or processes or nodes rather than just one). The only constraint(约束) is that services must be stateless, all state being in the request or in some shared storage such as a database.

Figure 15 - Request Distribution

There are two ways to connect multiple clients to multiple servers. The brute(畜生) force way is to connect each client socket(插座) to multiple service endpoints(端点). One client socket can connect to multiple service sockets, and the REQ socket will then distribute(分配) requests among these services. Let's say you connect a client socket to three service endpoints; A, B, and C. The client makes requests R1, R2, R3, R4. R1 and R4 go to service A, R2 goes to B, and R3 goes to service C.

This design lets you add more clients cheaply. You can also add more services. Each client will distribute its requests to the services. But each client has to know the service topology(拓扑学). If you have 100 clients and then you decide to add three more services, you need to reconfigure(重新配置) and restart(重新启动) 100 clients in order for the clients to know about the three new services.

That's clearly not the kind of thing we want to be doing at 3 a.m. when our supercomputing(超级计算) cluster(群) has run out of resources and we desperately(拼命地) need to add a couple of hundred of new service nodes. Too many static pieces are like liquid concrete(具体物): knowledge is distributed and the more static pieces you have, the more effort it is to change the topology. What we want is something sitting in between clients and services that centralizes(集中) all knowledge of the topology. Ideally(理想的), we should be able to add and remove services or clients at any time without touching any other part of the topology.

So we'll write a little message queuing broker that gives us this flexibility(灵活性). The broker binds(捆绑) to two endpoints, a frontend(前端) for clients and a backend for services. It then uses zmq_poll() to monitor these two sockets for activity and when it has some, it shuttles messages between its two sockets. It doesn't actually manage any queues explicitly(明确的)—ZeroMQ does that automatically o(自动地)n each socket.

When you use REQ to talk to REP, you get a strictly synchronous(同步的) request-reply dialog. The client sends a request. The service reads the request and sends a reply. The client then reads the reply. If either the client or the service try to do anything else (e.g., sending two requests in a row without waiting for a response), they will get an error.

But our broker has to be nonblocking. Obviously, we can use zmq_poll() to wait for activity on either socket, but we can't use REP and REQ.

Figure 16 - Extended(延伸) Request-Reply

Luckily, there are two sockets called DEALER and ROUTER that let you do nonblocking request-response. You'll see in Chapter 3 - Advanced Request-Reply Patterns how DEALER and ROUTER sockets let you build all kinds of asynchronous(异步的) request-reply flows. For now, we're just going to see how DEALER and ROUTER let us extend REQ-REP across an intermediary(中间的), that is, our little broker.

In this simple extended request-reply pattern, REQ talks to ROUTER and DEALER talks to REP. In between the DEALER and ROUTER, we have to have code (like our broker) that pulls messages off the one socket and shoves(推) them onto the other.

The request-reply broker binds to two endpoints, one for clients to connect to (the frontend socket) and one for workers to connect to (the backend). To test this broker, you will want to change your workers so they connect to the backend socket. Here is a client that shows what I mean:

Here is the worker:

And here is the broker, which properly handles multipart messages:

Figure 17 - Request-Reply Broker

Using a request-reply broker makes your client/server architectures(建筑学) easier to scale(衡量) because clients don't see workers, and workers don't see clients. The only static node is the broker in the middle.

It turns out that the core loop(环) in the previous section's rrbroker is very useful, and reusable(可重复使用的). It lets us build pub-sub forwarders and shared queues and other little intermediaries(中间人) with very little effort. ZeroMQ wraps(外套) this up in a single method, zmq_proxy():

The two (or three sockets(插座), if we want to capture data) must be properly connected, bound, and configured(配置). When we call the zmq_proxy method, it's exactly like starting the main loop of rrbroker. Let's rewrite the request-reply broker to call zmq_proxy, and re-badge this as an expensive-sounding "message queue" (people have charged houses for code that did less):

If you're like most ZeroMQ users, at this stage your mind is starting to think, "What kind of evil(邪恶的) stuff(东西) can I do if I plug random(随机的) socket(插座) types into the proxy(代理人)?" The short answer is: try it and work out what is happening. In practice, you would usually stick to ROUTER/DEALER, XSUB/XPUB, or PULL/PUSH.

A frequent request from ZeroMQ users is, "How do I connect my ZeroMQ network with technology X?" where X is some other networking or messaging technology.

Figure 18 - Pub-Sub Forwarder Proxy

The simple answer is to build a bridge. A bridge is a small application that speaks one protocol(协议) at one socket, and converts(皈依者) to/from a second protocol at another socket. A protocol interpreter(解释者), if you like. A common bridging problem in ZeroMQ is to bridge two transports or networks.

As an example, we're going to write a little proxy that sits in between a publisher and a set of subscribers(订阅), bridging two networks. The frontend(前端) socket (SUB) faces the internal(内部的) network where the weather server is sitting, and the backend (PUB) faces subscribers on the external(外部的) network. It subscribes to the weather service on the frontend socket, and republishes(再版) its data on the backend socket.

It looks very similar to the earlier proxy(代理人) example, but the key part is that the frontend(前端) and backend sockets(插座) are on two different networks. We can use this model for example to connect a multicast(多路广播) network (pgm transport) to a tcp publisher.

ZeroMQ's error handling philosophy(哲学) is a mix of fail-fast and resilience(恢复力). Processes, we believe, should be as vulnerable(易受攻击的) as possible to internal(内部的) errors, and as robust(强健的) as possible against external(外部的) attacks and errors. To give an analogy(类比), a living cell will self-destruct(自毁) if it detects(察觉) a single internal error, yet it will resist attack from the outside by all means possible.

Assertions(断言), which pepper the ZeroMQ code, are absolutely(绝对地) vital(至关重要的) to robust code; they just have to be on the right side of the cellular(细胞的) wall. And there should be such a wall. If it is unclear whether a fault is internal or external, that is a design flaw(瑕疵) to be fixed. In C/C++, assertions stop the application immediately with an error. In other languages, you may get exceptions(例外) or halts(停止).

When ZeroMQ detects(察觉) an external(外部的) fault it returns an error to the calling code. In some rare cases, it drops messages silently if there is no obvious strategy(战略) for recovering from the error.

In most of the C examples we've seen so far there's been no error handling. Real code should do error handling on every single ZeroMQ call. If you're using a language binding(结合) other than C, the binding may handle errors for you. In C, you do need to do this yourself. There are some simple rules, starting with POSIX conventions(大会):

• Methods that create objects return NULL if they fail.
• Methods that process data may return the number of bytes processed, or -1 on an error or failure.
• Other methods return 0 on success and -1 on an error or failure.
• The error code is provided in errno or zmq_errno().
• A descriptive(描写的) error text for logging is provided by zmq_strerror().

For example:

There are two main exceptional(异常的) conditions that you should handle as nonfatal(非致命的):

• When your code receives a message with the ZMQ_DONTWAIT option and there is no waiting data, ZeroMQ will return -1 and set errno to EAGAIN.

• When one thread calls zmq_ctx_destroy(), and other threads are still doing blocking work, the zmq_ctx_destroy() call closes the context(环境) and all blocking calls exit with -1, and errno set to ETERM.

In C/C++, asserts(维护) can be removed entirely in optimized(最佳化的) code, so don't make the mistake of wrapping(包) the whole ZeroMQ call in an assert(). It looks neat; then the optimizer removes all the asserts and the calls you want to make, and your application breaks in impressive(感人的) ways.

Figure 19 - Parallel(平行线) Pipeline(管道) with Kill Signaling

Let's see how to shut down a process cleanly. We'll take the parallel pipeline example from the previous section. If we've started a whole lot of workers in the background, we now want to kill them when the batch(一批) is finished. Let's do this by sending a kill message to the workers. The best place to do this is the sink because it really knows when the batch is done.

How do we connect the sink to the workers? The PUSH/PULL sockets(插座) are one-way only. We could switch(转换) to another socket type, or we could mix multiple socket flows. Let's try the latter: using a pub-sub model to send kill messages to the workers:

• The sink creates a PUB socket on a new endpoint(端点).
• Workers bind(绑) their input(投入) socket to this endpoint.
• When the sink detects(察觉) the end of the batch, it sends a kill to its PUB socket.
• When a worker detects this kill message, it exits.

It doesn't take much new code in the sink:

Here is the worker process, which manages two sockets (a PULL socket getting tasks, and a SUB socket getting control commands), using the zmq_poll() technique we saw earlier:

Here is the modified(改进的) sink application. When it's finished collecting results, it broadcasts a kill message to all workers:

Realistic(现实的) applications need to shut down cleanly when interrupted with Ctrl-C or another signal such as SIGTERM. By default, these simply kill the process, meaning messages won't be flushed(激动的), files won't be closed cleanly, and so on.

Here is how we handle a signal in various languages:

The program provides s_catch_signals(), which traps Ctrl-C (SIGINT) and SIGTERM. When either of these signals arrive, the s_catch_signals() handler sets the global variable(变量的) s_interrupted. Thanks to your signal handler, your application will not die automatically(自动地). Instead, you have a chance to clean up and exit gracefully(优雅地). You have to now explicitly(明确地) check for an interrupt and handle it properly. Do this by calling s_catch_signals() (copy this from interrupt.c) at the start of your main code. This sets up the signal handling. The interrupt will affect ZeroMQ calls as follows:

• If your code is blocking in a blocking call (sending a message, receiving a message, or polling(投票)), then when a signal arrives, the call will return with EINTR.
• Wrappers like s_recv() return NULL if they are interrupted.

So check for an EINTR return code, a NULL return, and/or s_interrupted.

Here is a typical(典型的) code fragment(碎片):

s_catch_signals ();
client = zmq_socket (...);
while (!s_interrupted) {
    char *message = s_recv (client);
    if (!message)
        break;          //  Ctrl-C used
}
zmq_close (client);

If you call s_catch_signals() and don't test for interrupts, then your application will become immune(免疫者) to Ctrl-C and SIGTERM, which may be useful, but is usually not.

Any long-running application has to manage memory correctly, or eventually(最后的) it'll use up all available memory and crash. If you use a language that handles this automatically(自动地) for you, congratulations. If you program in C or C++ or any other language where you're responsible(负责的) for memory management, here's a short tutorial(辅导的) on using valgrind, which among other things will report on any leaks your programs have.

• To install(安装) valgrind, e.g., on Ubuntu or Debian, issue this command:

sudo apt-get install valgrind

• By default, ZeroMQ will cause valgrind to complain a lot. To remove these warnings, create a file called vg.supp that contains this:

{
   <socketcall_sendto>
   Memcheck:Param
   socketcall.sendto(msg)
   fun:send
   ...
}
{
   <socketcall_sendto>
   Memcheck:Param
   socketcall.send(msg)
   fun:send
   ...
}

• Fix your applications to exit cleanly after Ctrl-C. For any application that exits by itself, that's not needed, but for long-running applications, this is essential, otherwise valgrind will complain about all currently allocated(分配) memory.

• Build your application with -DDEBUG if it's not your default setting. That ensures(保证) valgrind can tell you exactly where memory is being leaked.

• Finally, run valgrind thus:

valgrind --tool=memcheck --leak-check=full --suppressions=vg.supp someprog

And after fixing any errors it reported, you should get the pleasant message:

==30536== ERROR SUMMARY: 0 errors from 0 contexts...

ZeroMQ is perhaps the nicest way ever to write multithreaded (MT) applications. Whereas(然而) ZeroMQ sockets(插座) require some readjustment(重新调整) if you are used to traditional sockets, ZeroMQ multithreading will take everything you know about writing MT applications, throw it into a heap in the garden, pour gasoline(汽油) over it, and set it alight(下来). It's a rare book that deserves burning, but most books on concurrent(并发的) programming do.

To make utterly(完全地) perfect MT programs (and I mean that literally(文字的)), we don't need mutexes(互斥), locks, or any other form of inter-thread communication except messages sent across ZeroMQ sockets.

By "perfect MT programs", I mean code that's easy to write and understand, that works with the same design approach(方法) in any programming language, and on any operating system, and that scales(天平) across any number of CPUs with zero wait states and no point of diminishing(逐渐缩小的) returns.

If you've spent years learning tricks to make your MT code work at all, let alone rapidly, with locks and semaphores(信号) and critical(鉴定的) sections, you will be disgusted(厌恶的) when you realize it was all for nothing. If there's one lesson we've learned from 30+ years of concurrent programming, it is: just don't share state. It's like two drunkards(酒鬼) trying to share a beer. It doesn't matter if they're good buddies(伙伴). Sooner or later, they're going to get into a fight. And the more drunkards you add to the table, the more they fight each other over the beer. The tragic(悲剧的) majority of MT applications look like drunken(喝醉的) bar fights.

The list of weird(怪异的) problems that you need to fight as you write classic(经典的) shared-state MT code would be hilarious(欢闹的) if it didn't translate directly into stress(压力) and risk(风险), as code that seems to work suddenly fails under pressure. A large firm with world-beating experience in buggy(童车) code released its list of "11 Likely Problems In Your Multithreaded Code", which covers forgotten synchronization(同步), incorrect granularity(间隔尺寸), read and write tearing, lock-free reordering(再订购), lock convoys(护送), two-step dance, and priority(优先) inversion(倒置).

Yeah, we counted seven problems, not eleven. That's not the point though. The point is, do you really want that code running the power grid or stock market to start getting two-step lock convoys at 3 p.m. on a busy Thursday? Who cares what the terms actually mean? This is not what turned us on to programming, fighting ever more complex(复杂的) side effects with ever more complex hacks.

Some widely used models, despite(尽管) being the basis(基础) for entire industries, are fundamentally(根本地) broken, and shared state concurrency(并发性) is one of them. Code that wants to scale without limit does it like the Internet does, by sending messages and sharing nothing except a common contempt(轻视) for broken programming models.

You should follow some rules to write happy multithreaded code with ZeroMQ:

• Isolate(隔离) data privately within its thread and never share data in multiple threads. The only exception(例外) to this are ZeroMQ contexts(环境), which are threadsafe.

• Stay away from the classic concurrency mechanisms(机制) like as mutexes, critical sections, semaphores, etc. These are an anti-pattern in ZeroMQ applications.

• Create one ZeroMQ context at the start of your process, and pass that to all threads that you want to connect via inproc sockets.

• Use attached threads to create structure(结构) within your application, and connect these to their parent threads using PAIR sockets(插座) over inproc. The pattern is: bind(绑) parent socket, then create child thread which connects its socket.

• Use detached threads to simulate(模仿的) independent tasks, with their own contexts(环境). Connect these over tcp. Later you can move these to stand-alone processes without changing the code significantly(意味深长地).

• All interaction(相互作用) between threads happens as ZeroMQ messages, which you can define(定义) more or less formally(正式地).

• Don't share ZeroMQ sockets between threads. ZeroMQ sockets are not threadsafe. Technically it's possible to migrate(移动) a socket from one thread to another but it demands skill. The only place where it's remotely(遥远的) sane(健全的) to share sockets between threads are in language bindings that need to do magic like garbage collection on sockets.

If you need to start more than one proxy(代理人) in an application, for example, you will want to run each in their own thread. It is easy to make the error of creating the proxy frontend(前端) and backend sockets in one thread, and then passing the sockets to the proxy in another thread. This may appear to work at first but will fail randomly(随便地) in real use. Remember: Do not use or close sockets except in the thread that created them.

If you follow these rules, you can quite easily build elegant(高雅的) multithreaded applications, and later split off threads into separate processes as you need to. Application logic(逻辑) can sit in threads, processes, or nodes: whatever your scale(规模) needs.

ZeroMQ uses native OS threads rather than virtual(虚拟的) "green" threads. The advantage is that you don't need to learn any new threading API, and that ZeroMQ threads map cleanly to your operating system. You can use standard tools like Intel's ThreadChecker to see what your application is doing. The disadvantages are that native threading APIs are not always portable, and that if you have a huge number of threads (in the thousands), some operating systems will get stressed(强调).

Let's see how this works in practice. We'll turn our old Hello World server into something more capable(能干的). The original server ran in a single thread. If the work per request is low, that's fine: one ØMQ thread can run at full speed on a CPU core, with no waits, doing an awful (可怕的)lot of work. But realistic (现实的)servers have to do nontrivial (非平凡的)work per request. A single core may not be enough when 10,000 clients hit the server all at once. So a realistic server will start multiple worker threads. It then accepts requests as fast as it can and distributes (分配)these to its worker threads. The worker threads grind (磨碎)through the work and eventually (最后)send their replies back.

You can, of course, do all this using a proxy broker and external(外部的) worker processes, but often it's easier to start one process that gobbles(火鸡叫声) up sixteen cores than sixteen processes, each gobbling up one core. Further, running workers as threads will cut out a network hop, latency(潜伏), and network traffic.

The MT version of the Hello World service basically(主要地) collapses(倒塌) the broker and workers into a single process:

Figure 20 - Multithreaded Server

All the code should be recognizable(可辨认的) to you by now. How it works:

• The server starts a set of worker threads. Each worker thread creates a REP socket(插座) and then processes requests on this socket. Worker threads are just like single-threaded servers. The only differences are the transport (inproc instead of tcp), and the bind-connect direction.

• The server creates a ROUTER socket to talk to clients and binds(捆绑) this to its external(外部的) interface(界面) (over tcp).

• The server creates a DEALER socket to talk to the workers and binds this to its internal(内部的) interface (over inproc).

• The server starts a proxy(代理人) that connects the two sockets. The proxy pulls incoming requests fairly from all clients, and distributes(分配) those out to workers. It also routes(路由) replies back to their origin.

Note that creating threads is not portable in most programming languages. The POSIX library is pthreads, but on Windows you have to use a different API. In our example, the pthread_create call starts up a new thread running the worker_routine function we defined(定义). We'll see in Chapter 3 - Advanced Request-Reply Patterns how to wrap(包) this in a portable API.

Here the "work" is just a one-second pause. We could do anything in the workers, including talking to other nodes. This is what the MT server looks like in terms of ØMQ sockets (插座)and nodes. Note how the request-reply chain is REQ-ROUTER-queue-DEALER-REP.

When you start making multithreaded applications with ZeroMQ, you'll encounter(遭遇) the question of how to coordinate(调整) your threads. Though you might be tempted(诱惑) to insert "sleep" statements(声明), or use multithreading techniques such as semaphores(信号) or mutexes(互斥), the only mechanism(机制) that you should use are ZeroMQ messages. Remember the story of The Drunkards and The Beer Bottle.

Let's make three threads that signal each other when they are ready. In this example, we use PAIR sockets over the inproc transport:

Figure 21 - The Relay Race

This is a classic(经典的) pattern for multithreading with ZeroMQ:

1. Two threads communicate over inproc, using a shared context(环境).
2. The parent thread creates one socket(插座), binds(捆绑) it to an inproc:// endpoint, and then starts the child thread, passing the context(环境) to it.
3. The child thread creates the second socket(插座), connects it to that inproc:// endpoint, and then signals to the parent thread that it's ready.

Note that multithreading code using this pattern is not scalable(可攀登的) out to processes. If you use inproc and socket pairs, you are building a tightly-bound application, i.e., one where your threads are structurally(在结构上) interdependent(相互依赖的). Do this when low latency(潜伏) is really vital(至关重要的). The other design pattern is a loosely bound application, where threads have their own context and communicate over ipc or tcp. You can easily break loosely bound threads into separate processes.

This is the first time we've shown an example using PAIR sockets. Why use PAIR? Other socket combinations(结合) might seem to work, but they all have side effects that could interfere(干涉) with signaling:

• You can use PUSH for the sender and PULL for the receiver. This looks simple and will work, but remember that PUSH will distribute(分配) messages to all available receivers. If you by accident start two receivers (e.g., you already have one running and you start a second), you'll "lose" half of your signals. PAIR has the advantage of refusing more than one connection; the pair is exclusive.

• You can use DEALER for the sender and ROUTER for the receiver. ROUTER, however, wraps(外套) your message in an "envelope", meaning your zero-size signal turns into a multipart message. If you don't care about the data and treat anything as a valid signal, and if you don't read more than once from the socket, that won't matter. If, however, you decide to send real data, you will suddenly find ROUTER providing you with "wrong" messages. DEALER also distributes outgoing(外出的) messages, giving the same risk(风险) as PUSH.

• You can use PUB for the sender and SUB for the receiver. This will correctly deliver your messages exactly as you sent them and PUB does not distribute as PUSH or DEALER do. However, you need to configure(安装) the subscriber(订户) with an empty subscription(捐献), which is annoying.

For these reasons, PAIR makes the best choice for coordination(协调) between pairs of threads.

When you want to coordinate(调整) a set of nodes on a network, PAIR sockets(插座) won't work well any more. This is one of the few areas where the strategies(战略) for threads and nodes are different. Principally(首要的), nodes come and go whereas(然而) threads are usually static. PAIR sockets do not automatically(自动地) reconnect(使再接合) if the remote(遥远的) node goes away and comes back.

Figure 22 - Pub-Sub Synchronization

The second significant(重大的) difference between threads and nodes is that you typically(代表性地) have a fixed number of threads but a more variable(变量的) number of nodes. Let's take one of our earlier scenarios(方案) (the weather server and clients) and use node coordination to ensure(保证) that subscribers(订阅) don't lose data when starting up.

This is how the application will work:

• The publisher knows in advance how many subscribers it expects. This is just a magic number it gets from somewhere.

• The publisher starts up and waits for all subscribers to connect. This is the node coordination part. Each subscriber subscribes and then tells the publisher it's ready via another socket.

• When the publisher has all subscribers connected, it starts to publish data.

In this case, we'll use a REQ-REP socket flow to synchronize(合拍) subscribers and publisher. Here is the publisher:

And here is the subscriber(订户):

This Bash shell(壳) script will start ten subscribers(订阅) and then the publisher:

echo "Starting subscribers..."
for ((a=0; a<10; a++)); do
    syncsub &
done
echo "Starting publisher..."
syncpub

Which gives us this satisfying output(输出):

Starting subscribers...
Starting publisher...
Received 1000000 updates
Received 1000000 updates
...
Received 1000000 updates
Received 1000000 updates

We can't assume(承担) that the SUB connect will be finished by the time the REQ/REP dialog is complete. There are no guarantees(保证) that outbound(出站) connects will finish in any order whatsoever(无论什么), if you're using any transport except inproc. So, the example does a brute(畜生) force sleep of one second between subscribing, and sending the REQ/REP synchronization(同步).

A more robust(强健的) model could be:

• Publisher opens PUB socket(插座) and starts sending "Hello" messages (not data).
• Subscribers connect SUB socket and when they receive a Hello message they tell the publisher via a REQ/REP socket pair.
• When the publisher has had all the necessary confirmations(确认), it starts to send real data.

ZeroMQ's message API lets you send and receive messages directly from and to application buffers(有软皮摩擦) without copying data. We call this zero-copy, and it can improve performance in some applications.

You should think about using zero-copy in the specific(特殊的) case where you are sending large blocks of memory (thousands of bytes), at a high frequency(频率). For short messages, or for lower message rates, using zero-copy will make your code messier and more complex(复杂的) with no measurable(可测量的) benefit(利益). Like all optimizations(最佳化), use this when you know it helps, and measure before and after.

To do zero-copy, you use zmq_msg_init_data() to create a message that refers to a block of data already allocated(分配) with malloc() or some other allocator(分配算符), and then you pass that to zmq_msg_send(). When you create the message, you also pass a function that ZeroMQ will call to free the block of data, when it has finished sending the message. This is the simplest example, assuming(承担) buffer is a block of 1,000 bytes allocated on the heap:

Note that you don't call zmq_msg_close() after sending a message—libzmq will do this automatically(自动地) when it's actually done sending the message.

There is no way to do zero-copy on receive: ZeroMQ delivers you a buffer(缓冲区) that you can store as long as you wish, but it will not write data directly into application buffers.

On writing, ZeroMQ's multipart messages work nicely together with zero-copy. In traditional messaging, you need to marshal(元帅) different buffers together into one buffer that you can send. That means copying data. With ZeroMQ, you can send multiple buffers coming from different sources as individual(个人的) message frames(框架). Send each field as a length-delimited frame. To the application, it looks like a series of send and receive calls. But internally(内部地), the multiple parts get written to the network and read back with single system calls, so it's very efficient(有效率的).

In the pub-sub pattern, we can split the key into a separate message frame that we call an envelope. If you want to use pub-sub envelopes, make them yourself. It's optional(可选择的), and in previous pub-sub examples we didn't do this. Using a pub-sub envelope is a little more work for simple cases, but it's cleaner especially for real cases, where the key and the data are naturally separate things.

Figure 23 - Pub-Sub Envelope with Separate Key

Subscriptions(捐献) do a prefix(前缀) match. That is, they look for "all messages starting with XYZ". The obvious question is: how to delimit(划界) keys from data so that the prefix match doesn't accidentally(意外地) match data. The best answer is to use an envelope because the match won't cross a frame boundary(边界). Here is a minimalist(极简抽象派艺术的) example of how pub-sub envelopes look in code. This publisher sends messages of two types, A and B.

The envelope holds the message type:

The subscriber(订户) wants only messages of type B:

When you run the two programs, the subscriber(订户) should show you this:

[B] We would like to see this
[B] We would like to see this
[B] We would like to see this
...

This example shows that the subscription(捐献) filter rejects or accepts the entire multipart message (key plus data). You won't get part of a multipart message, ever. If you subscribe to multiple publishers and you want to know their address so that you can send them data via another socket(插座) (and this is a typical(典型的) use case), create a three-part message.

Figure 24 - Pub-Sub Envelope with Sender Address

When you can send messages rapidly from process to process, you soon discover that memory is a precious resource, and one that can be trivially(琐细地) filled up. A few seconds of delay somewhere in a process can turn into a backlog(积压的工作) that blows up a server unless you understand the problem and take precautions(预防).

The problem is this: imagine you have process A sending messages at high frequency(频率) to process B, which is processing them. Suddenly B gets very busy (garbage collection, CPU overload, whatever), and can't process the messages for a short period. It could be a few seconds for some heavy garbage collection, or it could be much longer, if there's a more serious problem. What happens to the messages that process A is still trying to send frantically(疯狂似地)? Some will sit in B's network buffers(有软皮摩擦). Some will sit on the Ethernet wire itself. Some will sit in A's network buffers. And the rest will accumulate(积攒) in A's memory, as rapidly as the application behind A sends them. If you don't take some precaution, A can easily run out of memory and crash.

It is a consistent(始终如一的), classic(经典的) problem with message brokers. What makes it hurt more is that it's B's fault, superficially(表面地), and B is typically a user-written application which A has no control over.

What are the answers? One is to pass the problem upstream(上游部门). A is getting the messages from somewhere else. So tell that process, "Stop!" And so on. This is called flow control. It sounds plausible(貌似可信的), but what if you're sending out a Twitter feed? Do you tell the whole world to stop tweeting while B gets its act together?

Flow control works in some cases, but not in others. The transport layer can't tell the application layer to "stop" any more than a subway(地铁) system can tell a large business, "please keep your staff(职员) at work for another half an hour. I'm too busy". The answer for messaging is to set limits on the size of buffers(有软皮摩擦), and then when we reach those limits, to take some sensible(明智的) action. In some cases (not for a subway system, though), the answer is to throw away messages. In others, the best strategy(战略) is to wait.

ZeroMQ uses the concept(观念) of HWM (high-water mark) to define(定义) the capacity(能力) of its internal(内部的) pipes. Each connection out of a socket(插座) or into a socket has its own pipe, and HWM for sending, and/or receiving, depending on the socket type. Some sockets (PUB, PUSH) only have send buffers. Some (SUB, PULL, REQ, REP) only have receive buffers. Some (DEALER, ROUTER, PAIR) have both send and receive buffers.

In ZeroMQ v2.x, the HWM was infinite(无限的) by default. This was easy but also typically(代表性地) fatal(致命的) for high-volume(大容量) publishers. In ZeroMQ v3.x, it's set to 1,000 by default, which is more sensible. If you're still using ZeroMQ v2.x, you should always set a HWM on your sockets, be it 1,000 to match ZeroMQ v3.x or another figure that takes into account your message sizes and expected subscriber(订户) performance.

When your socket reaches its HWM, it will either block or drop data depending on the socket type. PUB and ROUTER sockets will drop data if they reach their HWM, while other socket types will block. Over the inproc transport, the sender and receiver share the same buffers, so the real HWM is the sum of the HWM set by both sides.

Lastly, the HWMs are not exact; while you may get up to 1,000 messages by default, the real buffer size may be much lower (as little as half), due to the way libzmq implements its queues.

As you build applications with ZeroMQ, you will come across this problem more than once: losing messages that you expect to receive. We have put together a diagram that walks through the most common causes for this.

Figure 25 - Missing Message Problem Solver

Here's a summary of what the graphic(图表的) says:

• On SUB sockets, set a subscription(捐献) using zmq_setsockopt() with ZMQ_SUBSCRIBE, or you won't get messages. Because you subscribe(签署) to messages by prefix(前缀), if you subscribe to "" (an empty subscription(捐献)), you will get everything.

• If you start the SUB socket(插座) (i.e., establish(建立) a connection to a PUB socket) after the PUB socket has started sending out data, you will lose whatever it published before the connection was made. If this is a problem, set up your architecture(建筑学) so the SUB socket starts first, then the PUB socket starts publishing.

• Even if you synchronize(合拍) a SUB and PUB socket, you may still lose messages. It's due to the fact that internal(内部的) queues aren't created until a connection is actually created. If you can switch(转换) the bind(捆绑)/connect direction so the SUB socket binds, and the PUB socket connects, you may find it works more as you'd expect.

• If you're using REP and REQ sockets, and you're not sticking to the synchronous(同步的) send/recv/send/recv order, ZeroMQ will report errors, which you might ignore(驳回诉讼). Then, it would look like you're losing messages. If you use REQ or REP, stick to the send/recv order, and always, in real code, check for errors on ZeroMQ calls.

• If you're using PUSH sockets, you'll find that the first PULL socket to connect will grab an unfair share of messages. The accurate(精确的) rotation(旋转) of messages only happens when all PULL sockets are successfully connected, which can take some milliseconds(毫秒). As an alternative(二中择一) to PUSH/PULL, for lower data rates, consider using ROUTER/DEALER and the load balancing pattern.

• If you're sharing sockets across threads, don't. It will lead to random(随机的) weirdness(命运), and crashes.

• If you're using inproc, make sure both sockets are in the same context(环境). Otherwise the connecting side will in fact fail. Also, bind first, then connect. inproc is not a disconnected(分离的) transport like tcp.

• If you're using ROUTER sockets, it's remarkably(卓越的) easy to lose messages by accident, by sending malformed(畸形的) identity(身份) frames(框架) (or forgetting to send an identity frame). In general setting the ZMQ_ROUTER_MANDATORY option on ROUTER sockets(插座) is a good idea, but do also check the return code on every send call.

• Lastly, if you really can't figure out what's going wrong, make a minimal test case that reproduces(复制) the problem, and ask for help from the ZeroMQ community.

In Chapter 2 - Sockets and Patterns we worked through the basics of using ZeroMQ by developing a series of small applications, each time exploring new aspects(方面) of ZeroMQ. We'll continue this approach(方法) in this chapter as we explore advanced patterns built on top of ZeroMQ's core request-reply pattern.

We'll cover:

• How the request-reply mechanisms(机制) work
• How to combine REQ, REP, DEALER, and ROUTER sockets
• How ROUTER sockets work, in detail
• The load balancing pattern
• Building a simple load balancing message broker
• Designing a high-level API for ZeroMQ
• Building an asynchronous(异步的) request-reply server
• A detailed inter-broker routing(路由选择) example

We already looked briefly at multipart messages. Let's now look at a major use case, which is reply message envelopes. An envelope is a way of safely packaging up data with an address, without touching the data itself. By separating reply addresses into an envelope we make it possible to write general purpose intermediaries(中间人) such as APIs and proxies(代理人) that create, read, and remove addresses no matter what the message payload(有效载荷) or structure(结构) is.

In the request-reply pattern, the envelope holds the return address for replies. It is how a ZeroMQ network with no state can create round-trip request-reply dialogs.

When you use REQ and REP sockets(插座) you don't even see envelopes; these sockets deal with them automatically(自动地). But for most of the interesting request-reply patterns, you'll want to understand envelopes and particularly ROUTER sockets. We'll work through this step-by-step(按部就班的).

A request-reply exchange consists of a request message, and an eventual(最后的) reply message. In the simple request-reply pattern, there's one reply for each request. In more advanced patterns, requests and replies can flow asynchronously(异步的). However, the reply envelope always works the same way.

The ZeroMQ reply envelope formally(正式地) consists of zero or more reply addresses, followed by an empty frame(框架) (the envelope delimiter(划界)), followed by the message body (zero or more frames). The envelope is created by multiple sockets working together in a chain. We'll break this down.

We'll start by sending "Hello" through a REQ socket. The REQ socket creates the simplest possible reply envelope, which has no addresses, just an empty delimiter frame and the message frame containing the "Hello" string. This is a two-frame message.

Figure 26 - Request with Minimal Envelope

The REP socket(插座) does the matching work: it strips(带) off the envelope, up to and including the delimiter(划界) frame(框架), saves the whole envelope, and passes the "Hello" string up the application. Thus our original Hello World example used request-reply envelopes internally(内部地), but the application never saw them.

If you spy on the network data flowing between hwclient and hwserver, this is what you'll see: every request and every reply is in fact two frames, an empty frame and then the body. It doesn't seem to make much sense for a simple REQ-REP dialog. However you'll see the reason when we explore how ROUTER and DEALER handle envelopes.

Now let's extend the REQ-REP pair with a ROUTER-DEALER proxy(代理人) in the middle and see how this affects the reply envelope. This is the extended request-reply pattern we already saw in Chapter 2 - Sockets and Patterns. We can, in fact, insert any number of proxy steps. The mechanics(力学) are the same.

Figure 27 - Extended Request-Reply Pattern

The proxy does this, in pseudo-code:

prepare context, frontend and backend sockets
while true:
    poll on both sockets
    if frontend had input:
        read all frames from frontend
        send to backend
    if backend had input:
        read all frames from backend
        send to frontend

The ROUTER socket, unlike other sockets, tracks every connection it has, and tells the caller about these. The way it tells the caller is to stick the connection identity in front of each message received. An identity(身份), sometimes called an address, is just a binary(二进制的) string with no meaning except "this is a unique(独特的) handle to the connection". Then, when you send a message via a ROUTER socket(插座), you first send an identity frame(框架).

The zmq_socket() man page describes it thus:

When receiving messages a ZMQ_ROUTER socket shall prepend(预先考虑) a message part containing the identity of the originating(起源的) peer(贵族) to the message before passing it to the application. Messages received are fair-queued from among all connected peers. When sending messages a ZMQ_ROUTER socket shall remove the first part of the message and use it to determine the identity of the peer the message shall be routed(已选择路径) to.

As a historical(历史的) note, ZeroMQ v2.2 and earlier use UUIDs as identities. ZeroMQ v3.0 and later generate(形成) a 5 byte identity by default (0 + a random(随机的) 32bit integer(整数)). There's some impact(影响) on network performance, but only when you use multiple proxy(代理人) hops(蜱酒花), which is rare. Mostly the change was to simplify(简化) building libzmq by removing the dependency(属国) on a UUID library.

Identities are a difficult concept(观念) to understand, but it's essential if you want to become a ZeroMQ expert. The ROUTER socket invents a random identity for each connection with which it works. If there are three REQ sockets connected to a ROUTER socket, it will invent three random identities, one for each REQ socket.

So if we continue our worked example, let's say the REQ socket has a 3-byte identity ABC. Internally(内部的), this means the ROUTER socket keeps a hash table where it can search for ABC and find the TCP connection for the REQ socket.

When we receive the message off the ROUTER socket, we get three frames.

Figure 28 - Request with One Address

The core of the proxy(代理人) loop(环) is "read from one socket(插座), write to the other", so we literally(照字面地) send these three frames(框架) out on the DEALER socket. If you now sniffed(嗅) the network traffic, you would see these three frames flying from the DEALER socket to the REP socket. The REP socket does as before, strips(带) off the whole envelope including the new reply address, and once again delivers the "Hello" to the caller.

Incidentally(附带的) the REP socket can only deal with one request-reply exchange at a time, which is why if you try to read multiple requests or send multiple replies without sticking to a strict recv-send cycle, it gives an error.

You should now be able to visualize(形象) the return path. When hwserver sends "World" back, the REP socket wraps(外套) that with the envelope it saved, and sends a three-frame reply message across the wire to the DEALER socket.

Figure 29 - Reply with one Address

Now the DEALER reads these three frames, and sends all three out via the ROUTER socket. The ROUTER takes the first frame for the message, which is the ABC identity(身份), and looks up the connection for this. If it finds that, it then pumps the next two frames out onto the wire.

Figure 30 - Reply with Minimal Envelope

The REQ socket picks this message up, and checks that the first frame is the empty delimiter(划界), which it is. The REQ socket discards(抛弃) that frame and passes "World" to the calling application, which prints it out to the amazement(惊异) of the younger us looking at ZeroMQ for the first time.

To be honest, the use cases for strict request-reply or extended(延伸) request-reply are somewhat limited. For one thing, there's no easy way to recover from common failures like the server crashing due to buggy(童车) application code. We'll see more about this in Chapter 4 - Reliable(可靠的) Request-Reply Patterns. However once you grasp(抓住) the way these four sockets deal with envelopes, and how they talk to each other, you can do very useful things. We saw how ROUTER uses the reply envelope to decide which client REQ socket to route(按某路线发送) a reply back to. Now let's express this another way:

• Each time ROUTER gives you a message, it tells you what peer(贵族) that came from, as an identity.
• You can use this with a hash table (with the identity as key) to track new peers as they arrive.
• ROUTER will route(路线) messages asynchronously(异步的) to any peer(贵族) connected to it, if you prefix(加前缀) the identity(身份) as the first frame(框架) of the message.

ROUTER sockets(插座) don't care about the whole envelope. They don't know anything about the empty delimiter(划界). All they care about is that one identity frame that lets them figure out which connection to send a message to.

Let's recap this:

• The REQ socket sends, to the network, an empty delimiter frame in front of the message data. REQ sockets are synchronous(同步的). REQ sockets always send one request and then wait for one reply. REQ sockets talk to one peer at a time. If you connect a REQ socket to multiple peers, requests are distributed(分布式的) to and replies expected from each peer one turn at a time.

• The REP socket reads and saves all identity frames up to and including the empty delimiter, then passes the following frame or frames to the caller. REP sockets are synchronous and talk to one peer at a time. If you connect a REP socket to multiple peers, requests are read from peers in fair fashion, and replies are always sent to the same peer that made the last request.

• The DEALER socket is oblivious(遗忘的) to the reply envelope and handles this like any multipart message. DEALER sockets are asynchronous and like PUSH and PULL combined. They distribute sent messages among all connections, and fair-queue received messages from all connections.

• The ROUTER socket is oblivious to the reply envelope, like DEALER. It creates identities for its connections, and passes these identities to the caller as a first frame in any received message. Conversely(相反的), when the caller sends a message, it uses the first message frame as an identity to look up the connection to send to. ROUTERS are asynchronous.

We have four request-reply sockets, each with a certain behavior(行为). We've seen how they connect in simple and extended(延伸) request-reply patterns. But these sockets are building blocks that you can use to solve many problems.

These are the legal(法律的) combinations(结合):

• REQ to REP
• DEALER to REP
• REQ to ROUTER
• DEALER to ROUTER
• DEALER to DEALER
• ROUTER to ROUTER

And these combinations(结合) are invalid(无效的) (and I'll explain why):

• REQ to REQ
• REQ to DEALER
• REP to REP
• REP to ROUTER

Here are some tips for remembering the semantics(语义学). DEALER is like an asynchronous(异步的) REQ socket(插座), and ROUTER is like an asynchronous REP socket. Where we use a REQ socket, we can use a DEALER; we just have to read and write the envelope ourselves. Where we use a REP socket, we can stick a ROUTER; we just need to manage the identities(身份) ourselves.

Think of REQ and DEALER sockets as "clients" and REP and ROUTER sockets as "servers". Mostly, you'll want to bind(绑) REP and ROUTER sockets, and connect REQ and DEALER sockets to them. It's not always going to be this simple, but it is a clean and memorable(显著的) place to start.

We've already covered a REQ client talking to a REP server but let's take one aspect(方面): the REQ client must initiate(开始) the message flow. A REP server cannot talk to a REQ client that hasn't first sent it a request. Technically, it's not even possible, and the API also returns an EFSM error if you try it.

Now, let's replace the REQ client with a DEALER. This gives us an asynchronous(异步的) client that can talk to multiple REP servers. If we rewrote(重写) the "Hello World" client using DEALER, we'd be able to send off any number of "Hello" requests without waiting for replies.

When we use a DEALER to talk to a REP socket(插座), we must accurately(精确地) emulate(仿真) the envelope that the REQ socket would have sent, or the REP socket will discard(抛弃) the message as invalid(无效的). So, to send a message, we:

• Send an empty message frame(框架) with the MORE flag set; then
• Send the message body.

And when we receive a message, we:

• Receive the first frame and if it's not empty, discard the whole message;
• Receive the next frame and pass that to the application.

In the same way that we can replace REQ with DEALER, we can replace REP with ROUTER. This gives us an asynchronous server that can talk to multiple REQ clients at the same time. If we rewrote the "Hello World" server using ROUTER, we'd be able to process any number of "Hello" requests in parallel(平行线). We saw this in the Chapter 2 - Sockets and Patterns mtserver example.

We can use ROUTER in two distinct(明显的) ways:

• As a proxy(代理人) that switches(开关) messages between frontend(前端) and backend sockets(插座).
• As an application that reads the message and acts on it.

In the first case, the ROUTER simply reads all frames(框架), including the artificial(人造的) identity(身份) frame, and passes them on blindly. In the second case the ROUTER must know the format of the reply envelope it's being sent. As the other peer(贵族) is a REQ socket, the ROUTER gets the identity frame, an empty frame, and then the data frame.

Now we can switch out both REQ and REP with DEALER and ROUTER to get the most powerful socket combination, which is DEALER talking to ROUTER. It gives us asynchronous(异步的) clients talking to asynchronous servers, where both sides have full control over the message formats.

Because both DEALER and ROUTER can work with arbitrary(任意的) message formats, if you hope to use these safely, you have to become a little bit of a protocol(协议) designer. At the very least you must decide whether you wish to emulate(仿真) the REQ/REP reply envelope. It depends on whether you actually need to send replies or not.

You can swap(与…交换) a REP with a ROUTER, but you can also swap a REP with a DEALER, if the DEALER is talking to one and only one peer.

When you replace a REP with a DEALER, your worker can suddenly go full asynchronous, sending any number of replies back. The cost is that you have to manage the reply envelopes yourself, and get them right, or nothing at all will work. We'll see a worked example later. Let's just say for now that DEALER to DEALER is one of the trickier(狡猾的) patterns to get right, and happily it's rare that we need it.

This sounds perfect for N-to-N connections, but it's the most difficult combination(结合) to use. You should avoid it until you are well advanced with ZeroMQ. We'll see one example it in the Freelance pattern in Chapter 4 - Reliable(可靠的) Request-Reply Patterns, and an alternative(供选择的) DEALER to ROUTER design for peer-to-peer(对等) work in Chapter 8 - A Framework for Distributed Computing.

Mostly, trying to connect clients to clients, or servers to servers is a bad idea and won't work. However, rather than give general vague(模糊的) warnings, I'll explain in detail:

• REQ to REQ: both sides want to start by sending messages to each other, and this could only work if you timed things so that both peers(撒尿) exchanged messages at the same time. It hurts my brain to even think about it.

• REQ to DEALER: you could in theory do this, but it would break if you added a second REQ because DEALER has no way of sending a reply to the original peer. Thus the REQ socket(插座) would get confused(混乱), and/or return messages meant for another client.

• REP to REP: both sides would wait for the other to send the first message.

• REP to ROUTER: the ROUTER socket can in theory initiate(开始) the dialog and send a properly-formatted request, if it knows the REP socket has connected and it knows the identity(身份) of that connection. It's messy and adds nothing over DEALER to ROUTER.

The common thread in this valid versus(对) invalid(无效的) breakdown(故障) is that a ZeroMQ socket connection is always biased(有偏见的) towards one peer that binds(捆绑) to an endpoint(端点), and another that connects to that. Further, that which side binds and which side connects is not arbitrary(任意的), but follows natural patterns. The side which we expect to "be there" binds: it'll be a server, a broker, a publisher, a collector(收藏家). The side that "comes and goes" connects: it'll be clients and workers. Remembering this will help you design better ZeroMQ architectures(建筑学).

Let's look at ROUTER sockets(插座) a little closer. We've already seen how they work by routing(路由选择) individual(个人的) messages to specific(特殊的) connections. I'll explain in more detail how we identify(确定) those connections, and what a ROUTER socket does when it can't send a message.

The identity concept(观念) in ZeroMQ refers specifically(特别地) to ROUTER sockets and how they identify the connections they have to other sockets. More broadly, identities(身份) are used as addresses in the reply envelope. In most cases, the identity is arbitrary(任意的) and local to the ROUTER socket: it's a lookup(查找) key in a hash table. Independently, a peer(贵族) can have an address that is physical (a network endpoint(端点) like "tcp://192.168.55.117:5670") or logical(合逻辑的) (a UUID or email address or other unique(独特的) key).

An application that uses a ROUTER socket to talk to specific peers can convert(转变) a logical address to an identity if it has built the necessary hash table. Because ROUTER sockets only announce the identity of a connection (to a specific peer) when that peer sends a message, you can only really reply to a message, not spontaneously(自发地) talk to a peer.

This is true even if you flip(弹) the rules and make the ROUTER connect to the peer rather than wait for the peer to connect to the ROUTER. However you can force the ROUTER socket to use a logical address in place of its identity. The zmq_setsockopt reference(参考) page calls this setting the socket identity. It works as follows:

• The peer application sets the ZMQ_IDENTITY option of its peer socket (DEALER or REQ) before binding or connecting.
• Usually the peer(贵族) then connects to the already-bound ROUTER socket(插座). But the ROUTER can also connect to the peer.
• At connection time, the peer socket tells the router(路由器) socket, "please use this identity(身份) for this connection".
• If the peer socket doesn't say that, the router generates(形成) its usual arbitrary(任意的) random(随机的) identity for the connection.
• The ROUTER socket now provides this logical(合逻辑的) address to the application as a prefix(前缀) identity frame(框架) for any messages coming in from that peer.
• The ROUTER also expects the logical address as the prefix identity frame for any outgoing(外出的) messages.

Here is a simple example of two peers that connect to a ROUTER socket, one that imposes(利用) a logical address "PEER2":

Here is what the program prints:

----------------------------------------
[005] 006B8B4567
[000]
[039] ROUTER uses a generated 5 byte identity
----------------------------------------
[005] PEER2
[000]
[038] ROUTER uses REQ's socket identity

ROUTER sockets(插座) do have a somewhat brutal(残忍的) way of dealing with messages they can't send anywhere: they drop them silently. It's an attitude that makes sense in working code, but it makes debugging(调试) hard. The "send identity(身份) as first frame(框架)" approach(方法) is tricky(狡猾的) enough that we often get this wrong when we're learning, and the ROUTER's stony(无情的) silence when we mess up isn't very constructive(建设性的).

Since ZeroMQ v3.2 there's a socket option you can set to catch this error: ZMQ_ROUTER_MANDATORY. Set that on the ROUTER socket and then when you provide an unroutable identity on a send call, the socket will signal an EHOSTUNREACH error.

Now let's look at some code. We'll see how to connect a ROUTER socket to a REQ socket, and then to a DEALER socket. These two examples follow the same logic(逻辑), which is a load balancing pattern. This pattern is our first exposure(暴露) to using the ROUTER socket for deliberate(故意的) routing(路由选择), rather than simply acting as a reply channel.

The load balancing pattern is very common and we'll see it several times in this book. It solves the main problem with simple round robin routing (as PUSH and DEALER offer) which is that round robin becomes inefficient(无效率的) if tasks do not all roughly take the same time.

It's the post office analogy(类比). If you have one queue per counter, and you have some people buying stamps (a fast, simple transaction(交易)), and some people opening new accounts (a very slow transaction), then you will find stamp buyers getting unfairly stuck in queues. Just as in a post office, if your messaging architecture(建筑学) is unfair, people will get annoyed.

The solution(解决方案) in the post office is to create a single queue so that even if one or two counters get stuck with slow work, other counters will continue to serve clients on a first-come, first-serve basis(基础).

One reason PUSH and DEALER use the simplistic(过分简单化的) approach(方法) is sheer(绝对的) performance. If you arrive in any major US airport, you'll find long queues of people waiting at immigration. The border patrol(巡逻) officials will send people in advance to queue up at each counter, rather than using a single queue. Having people walk fifty yards in advance saves a minute or two per passenger. And because every passport check takes roughly the same time, it's more or less fair. This is the strategy(战略) for PUSH and DEALER: send work loads ahead of time so that there is less travel distance.

This is a recurring(循环的) theme with ZeroMQ: the world's problems are diverse(不同的) and you can benefit(有益于) from solving different problems each in the right way. The airport isn't the post office and one size fits no one, really well.

Let's return to the scenario(方案) of a worker (DEALER or REQ) connected to a broker (ROUTER). The broker has to know when the worker is ready, and keep a list of workers so that it can take the least recently used worker each time.

The solution is really simple, in fact: workers send a "ready" message when they start, and after they finish each task. The broker reads these messages one-by-one. Each time it reads a message, it is from the last used worker. And because we're using a ROUTER socket(插座), we get an identity(身份) that we can then use to send a task back to the worker.

It's a twist(扭曲) on request-reply because the task is sent with the reply, and any response for the task is sent as a new request. The following code examples should make it clearer.

Here is an example of the load balancing pattern using a ROUTER broker talking to a set of REQ workers:

The example runs for five seconds and then each worker prints how many tasks they handled. If the routing(路由选择) worked, we'd expect a fair distribution(分布) of work:

Completed: 20 tasks
Completed: 18 tasks
Completed: 21 tasks
Completed: 23 tasks
Completed: 19 tasks
Completed: 21 tasks
Completed: 17 tasks
Completed: 17 tasks
Completed: 25 tasks
Completed: 19 tasks